Data analysis method based on Internet of Things interaction and cloud computing communication

Abstract

The present invention discloses a data analysis method based on Internet of Things interaction and cloud computing communication, relates to the field of cloud computing, and comprises the following steps: constructing a data analysis platform for data interaction and communication, and uploading data generated in the data interaction and communication process to the data analysis cloud platform; analyzing the data uploaded to the data analysis cloud platform, and judging the security level of the data according to the analysis result; processing the data uploaded to the data analysis cloud platform according to the security level of the data; solving and processing problems in a timely manner, improving users' understanding of data security, ensuring the security of interaction and communication data, and improving users' interaction and communication experience.

Description

Technical Field

[0001] The present invention relates to the technical field of cloud computing, and in particular to a data analysis method based on Internet of Things interaction and cloud computing communication. Background Art

[0002] Cloud computing is a type of distributed computing. It means breaking down huge data computing and processing services into multiple sub-services through the network "cloud", and then processing and analyzing these sub-services through a system composed of multiple servers, and obtaining corresponding data processing results. Cloud computing can significantly improve data processing efficiency and is increasingly widely used in today's big data era.

[0003] However, the existing technology has limitations for data analysis, and the interaction and communication data analysis problems are not handled in a timely manner. Therefore, a data analysis method based on Internet of Things interaction and cloud computing communication is provided. Summary of the invention

[0004] The purpose of the present invention is to provide a data analysis method based on Internet of Things interaction and cloud computing communication.

[0005] The object of the present invention can be achieved by the following technical solution: A data analysis method based on Internet of Things interaction and cloud computing communication comprises the following steps:

[0006] S1: Build a data analysis platform for data interaction and communication, and upload the data generated during the data interaction and communication process to the data analysis cloud platform;

[0007] S2: Analyze the data uploaded to the data analysis cloud platform and determine the security level of the data based on the analysis results;

[0008] S3: Process the data uploaded to the data analysis cloud platform according to the data security level.

[0009] Furthermore, the construction process of the data analysis cloud platform includes:

[0010] Use IoT technology and cloud computing technology to build a data analysis cloud platform;

[0011] A management center is arranged in the data analysis cloud platform, and the management center is communicatively connected with a service module, a data acquisition module, a data processing module, a data analysis module and a data storage module.

[0012] Furthermore, before uploading the data generated in the data interaction and communication process to the data analysis cloud platform, the process of users interacting and communicating through the service module includes:

[0013] Users must verify their personal identity information before interacting and communicating;

[0014] After completing the verification of personal identity information, the user obtains interaction and communication permissions, and performs interaction and communication behaviors within the service module. The interaction and communication data sets generated during the user interaction and communication process are obtained through the data acquisition module, and the generated interaction and communication data sets are processed through the data processing module.

[0015] Furthermore, the process of the processing module processing the interaction and communication data set includes:

[0016] Building an interaction and communication database based on the interaction and communication data obtained by the data acquisition module, and marking the interaction and communication database as an original database;

[0017] The interaction and communication data of the original database are cleaned.

[0018] Furthermore, the process of data analysis on the original database includes:

[0019] Randomly select m data from the original database and mark the m data as initial center points;

[0020] Mark all the data in the original database as sample points, and obtain the distance between the sample points and the m initial center points;

[0021] According to the distance between the obtained sample point and the m initial center points, the sample point is divided into the category corresponding to the initial center point closest to it;

[0022] After the classification is completed, the categories are marked as clusters and the center points of the clusters are re-determined;

[0023] The mean of the features of all sample points in the category is taken as the feature value corresponding to the new center point, and the feature value corresponding to the new center point is marked as the centroid;

[0024] And so on, until the points in each cluster no longer change;

[0025] According to the above steps, the clustering error value is obtained;

[0026] The safety level is determined by obtaining the clustering error value.

[0027] Furthermore, the process of judging the safety level according to the clustering error value includes:

[0028] Set the safety rating threshold Z>X>0;

[0029] When the clustering error value is less than or equal to the threshold X, the security level is high;

[0030] When the clustering error value is greater than the threshold X and less than or equal to the threshold Z, the security level is medium;

[0031] When the clustering error value is greater than the threshold Z, the security level is low.

[0032] Furthermore, the process of processing the data uploaded to the data analysis cloud platform according to the security level of the data includes:

[0033] Set up data storage space;

[0034] Set up the disk;

[0035] Set up storage units;

[0036] Issue early warning for data with low security level;

[0037] Divide data storage space according to the data type of data with high security level and data with low security level;

[0038] Sending the data with a high security level and the data with a low security level to corresponding data storage spaces for encryption to generate first encrypted data;

[0039] Compressing the first encrypted data to generate a first encrypted data block;

[0040] Writing the first encrypted data block into a data block on the disk;

[0041] The storage unit obtains data from the disk through a read operation;

[0042] decompressing the first encrypted data block in the storage unit and updating the decompressed data;

[0043] Compared with the prior art, the beneficial effects of the present invention are: using cloud computing technology to process and cluster the interaction and communication data, calculating the clustering error, solving the limitations of the prior art, analyzing the data through the calculated clustering error to check for data with a low security level, solving and processing problems in a timely manner, improving users' understanding of data security, ensuring the security of interaction and communication data, and improving users' experience of interaction and communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0045] like Figure 1 As shown, the data analysis method based on the interaction of the Internet of Things and cloud computing communication includes the following steps:

[0046] S1: Build a data analysis platform for data interaction and communication, and upload the data generated during the data interaction and communication process to the data analysis cloud platform;

[0047] S2: Analyze the data uploaded to the data analysis cloud platform and determine the security level of the data based on the analysis results;

[0048] S3: Process the data uploaded to the data analysis cloud platform according to the data security level.

[0049] It should be further explained that, in the specific implementation process, the construction process of the interactive and communication data analysis cloud platform includes:

[0050] Use IoT technology and cloud computing technology to build an interactive and communicative data analysis cloud platform;

[0051] A management center is set in the data analysis cloud platform, and the management center is connected to the service module, data acquisition module, data processing module, data analysis module and data storage module;

[0052] It should be further explained that, in the specific implementation process, before uploading the data generated in the data interaction and communication process to the data analysis cloud platform, the users interact and communicate through the service module. The specific process includes:

[0053] Set the registration port and login port;

[0054] Users must verify their personal identity information before interacting and communicating;

[0055] The user enters basic personal information into the registration port; it should be further explained that in the specific implementation process, basic personal information includes name, gender, age, email address, ID card and real-name authenticated mobile phone number;

[0056] Review the basic personal information entered by the user and generate a login account and password after the review is passed;

[0057] The user enters the service module of the data analysis cloud platform through the login port according to the generated login account and login password;

[0058] After completing personal identity information verification, users obtain interaction and communication permissions, conduct interaction and communication behaviors within the service module, and generate corresponding interaction and communication data sets based on the user's interaction and communication behaviors;

[0059] After completing the interactive communication, the user sends the generated interactive and communication data set to the data collection module of the interactive and communication data analysis cloud platform, and collects the data required for data analysis through the data collection module of the interactive and communication data analysis cloud platform;

[0060] It should be further explained that, in the specific implementation process, the process of processing the data required for data analysis includes:

[0061] Collect the interaction and communication data set sent to the data collection module of the interaction and communication data analysis cloud platform, build an interaction and communication database based on the collected interaction and communication data set, and mark the interaction and communication database as the original database; it should be further explained that in the specific implementation process, the original database includes the number of times and the comprehensive communication content;

[0062] Clean the interaction and communication data of the original database, remove the incomplete data in the original database, and mark the incomplete data as "dirty data";

[0063] It should be further explained that, in the specific implementation process, the process of cleaning the interaction and communication data of the original database includes:

[0064] According to data mining, an improved TANE algorithm is used to mine approximate functional dependencies from "dirty" data;

[0065] Strategy recommendation uses a sorting strategy based on the number of times and a comprehensive communication content sorting strategy to sort the mined approximate functional dependencies, and whether the approximate functional dependencies of interaction and communication data are effective cleaning rules;

[0066] If yes, then use the cleaning rule to detect and repair dirty data;

[0067] It should be further explained that, in the specific implementation process, the calculation process of the TANE algorithm includes:

[0068] Mark the first row of data in the original database as L1, and so on;

[0069] The original database is marked as R, and all interaction and communication data in the original database are marked as A;

[0070] It starts the search from a single attribute set and expands the attribute set layer by layer through set inclusion relations, that is, the TANE algorithm starts from L1 = {{A}|A∈R}, calculates L2 from L1, calculates L3 from L2, and so on;

[0071] When the algorithm processes a set X, it tests functional dependencies of the form X\{A}→A, where A∈X. This ensures that only non-trivial functional dependencies are considered;

[0072] Top-down can ensure that only the minimum functional dependencies are output, and it can also be used to effectively prune the search space;

[0073] Upload the collected raw database to the data processing module of the interactive and communication data analysis cloud platform for data processing;

[0074] It should be further explained that, in the specific implementation process, the process of processing the data of the original database includes:

[0075] The original database is processed using the K-means algorithm;

[0076] It should be further explained that, in the specific implementation process, the process of processing the original database by using the K-means algorithm includes:

[0077] Set i, i takes 1, 2, ...;

[0078] Randomly select m data from the original database and mark the m data as initial center points;

[0079] Mark all the data in the original database as sample points, and calculate the distance between the sample points and the m initial center points;

[0080] According to the calculated distance between the sample point and the m initial center points, the sample point is divided into the category corresponding to the initial center point closest to it;

[0081] After the classification is completed, the categories are marked as clusters and the center points of the clusters are re-determined;

[0082] The mean of the features of all sample points in the category is taken as the feature value corresponding to the new center point, and the feature value corresponding to the new center point is marked as the centroid;

[0083] And so on, until the points in each cluster no longer change;

[0084] The degree of aggregation of each cluster is determined by calculating the clustering error;

[0085] It should be further explained that, in the specific implementation process, the calculation process of the clustering error includes:

[0086]

[0087] Where Ci is the i-th cluster, p is the sample point in Ci, a is the centroid of C, and S is the clustering error value of all samples;

[0088] The clustering error value generated by the data processing module is sent to the data analysis module of the interactive and communication data analysis cloud platform for data analysis;

[0089] Analyze the security level of interaction and communication data through clustering error values, and generate early warnings for data with low security levels;

[0090] It should be further explained that, in the specific implementation process, the process of analyzing the security level of interaction and communication data includes:

[0091] Set T>0;

[0092] Set the safety rating threshold Z>X>0;

[0093] When the clustering error value is less than or equal to the threshold X, the aggregation degree of each cluster is high, the sample division is fine, the security is high, and the security level is high;

[0094] When the clustering error value is greater than the threshold X and less than or equal to the threshold Z, the aggregation degree of each cluster is medium, the security level is medium, and the security level is medium;

[0095] When the clustering error value is greater than the threshold Z, the aggregation degree of each cluster is low, the safety degree is low, the safety level is low, and dangerous warning data is generated;

[0096] Produce early warnings for data with low safety levels through the generated dangerous early warning data;

[0097] It should be further explained that, in the specific implementation process, the process of generating early warning for data with low security level includes:

[0098] Set the warning threshold H>0;

[0099] When the danger warning data is less than or equal to H, the interactive and communication data analysis cloud platform sends danger warning information to the user, and the user needs to confirm the danger warning information before continuing to interact and communicate;

[0100] When the danger warning information is greater than H, the interactive and communication data analysis cloud platform sends a danger warning information to the user, and the user can no longer interact and communicate within T days;

[0101] Sending high-security-level and medium-security-level data to the data storage module of the interactive and communication data analysis cloud platform for storage;

[0102] It should be further explained that, in the specific implementation process, the process of storing data with high security level and medium security level includes:

[0103] Set up data storage space;

[0104] Set up the disk;

[0105] Set up storage units;

[0106] Divide data storage space according to the data type of data with high security level and data with low security level;

[0107] Sending the data with a high security level and the data with a low security level to corresponding data storage spaces for encryption to generate first encrypted data;

[0108] Compressing the first encrypted data to generate a first encrypted data block;

[0109] Writing the first encrypted data block into a data block on the disk;

[0110] The storage unit obtains data from the disk through a read operation;

[0111] The first encrypted data block is decompressed in the storage unit, and the decompressed data is updated.

[0112] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A data analysis method based on Internet of Things interaction and cloud computing communication, characterized in that: The following steps are involved: S1: Build a data analysis platform for data interaction and communication, and upload the data generated during the data interaction and communication process to the data analysis cloud platform; S2: Analyze the data uploaded to the data analysis cloud platform and determine the security level of the data based on the analysis results; S3: Process the data uploaded to the data analysis cloud platform according to the data security level; The construction process of the data analysis cloud platform includes: Use IoT technology and cloud computing technology to build a data analysis cloud platform; A management center is set in the data analysis cloud platform, and the management center is connected to the service module, data acquisition module, data processing module, data analysis module and data storage module in communication; Before uploading the data generated during the data interaction and communication process to the data analysis cloud platform, the process of users interacting and communicating through the service module includes: Users must verify their personal identity information before interacting and communicating; After completing the personal identity information verification, the user obtains the interaction and communication authority, performs interaction and communication behaviors in the service module, obtains the interaction and communication data set generated during the user interaction and communication process through the data collection module, and processes the generated interaction and communication data set through the data processing module; The process of the processing module processing the interaction and communication data set includes: Building an interaction and communication database based on the interaction and communication data obtained by the data acquisition module, and marking the interaction and communication database as an original database; Clean the interaction and communication data of the original database; The process of data analysis on the original database includes: Randomly select m data from the original database and mark the m data as initial center points; Mark all the data in the original database as sample points, and obtain the distance between the sample points and the m initial center points; According to the distance between the obtained sample point and the m initial center points, the sample point is divided into the category corresponding to the initial center point closest to it; After the classification is completed, the categories are marked as clusters and the center points of the clusters are re-determined; The mean of the features of all sample points in the category is taken as the feature value corresponding to the new center point, and the feature value corresponding to the new center point is marked as the centroid; And so on, until the points in each cluster no longer change; Obtain the clustering error value according to the above steps; The calculation process of clustering error value includes: ; Where Ci is the i-th cluster, p is the sample point in Ci, a is the centroid of C, and S is the clustering error value of all samples; The safety level is determined by obtaining the clustering error value; The process of judging the safety level based on the clustering error value includes: Set the safety rating threshold Z>X>0; When the clustering error value is less than or equal to the threshold X, the security level is high; When the clustering error value is greater than the threshold X and less than or equal to the threshold Z, the security level is medium; When the clustering error value is greater than the threshold Z, the security level is low.

2. The data analysis method based on Internet of Things interaction and cloud computing communication according to claim 1 is characterized in that: The process of processing the data uploaded to the data analysis cloud platform according to the data security level includes: Set up data storage space; Set up the disk; Set up storage units; Issue early warning for data with low security level; Divide data storage space according to the data type of data with high security level and data with low security level; Sending the data with a high security level and the data with a low security level to corresponding data storage spaces for encryption to generate first encrypted data; Compressing the first encrypted data to generate a first encrypted data block; Writing the first encrypted data block into a data block on the disk; The storage unit obtains data from the disk through a read operation; The first encrypted data block is decompressed in the storage unit, and the decompressed data is updated.

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