A big data-based communication intelligent safety supervision system and method

Abstract

The application relates to the technical field of communication intelligent security, in particular to a communication intelligent security supervision system and method based on big data, which comprises a communication supervision system construction module, a communication target feature analysis module, a correlation relationship judgment module, a target intervention user evaluation and analysis module and an intervention reminding module; the communication supervision system construction module is used for constructing a communication supervision system taking users connected through a communication transmission protocol and communication data as monitoring subjects; the communication target feature analysis module is used for analyzing communication transmission data of the users and outputting communication target features; the correlation relationship judgment module is used for judging whether the communication target features and the communication location data have a correlation relationship; the target intervention user evaluation and analysis module is used for selecting an optimal safe communication environment to determine that a communication user corresponding to the optimal safe communication environment is a target intervention user; and the intervention reminding module is used for monitoring communication location data of the target intervention user in real time and reminding intervention.

Description

Technical Field

[0001] This invention relates to the field of intelligent communication security technology, specifically to a big data-based intelligent communication security monitoring system and method. Background Technology

[0002] In recent years, with the rapid development of the Internet and information technology, and the combination of servers and the Internet, intelligent communication supervision plays a vital role in communication data transmission. Existing technologies not only enable the monitoring of communication network quality, but also enable real-time monitoring of the entire communication architecture, thereby transforming the communication network, which is indispensable in daily life, into a communication monitoring system based on digital technology.

[0003] However, current communication monitoring systems focus on issues such as data transmission between different levels of the organizational structure in the communication architecture, without considering the intelligent control of users of the communication network. How to effectively use user data as a communication lead to complete the adaptive adjustment of the communication monitoring system under the premise of communication security is the main issue that needs to be studied. Summary of the Invention

[0004] The purpose of this invention is to provide a communication intelligent security supervision system and method based on big data, so as to solve the problems mentioned in the background art.

[0005] To address the aforementioned technical problems, this invention provides the following technical solution: a big data-based intelligent security monitoring method for communications, comprising the following analysis steps:

[0006] Step S1: Monitor the communication application terminals that use servers as relay stations and communication transmission protocols as bridges, and build a communication monitoring system with users connected by communication transmission protocols and communication data as the main monitoring subjects. The communication data includes communication transmission data, communication location data, and communication environment data. When a user generates communication data, the communication monitoring system requests monitoring permissions. After obtaining the user's monitoring permissions, it analyzes the communication transmission data of the user connected by the communication transmission protocol and outputs the communication target characteristics.

[0007] Step S2: Based on the characteristics of the communication target, determine whether there is a correlation between the characteristics of the communication target and the communication location data;

[0008] Step S3: When there is a correlation, the communication monitoring system obtains the communication environment data of the user connected by the communication transmission protocol, and selects the optimal secure communication environment to determine the communication user corresponding to the optimal secure communication environment as the target intervention user;

[0009] Step S4: The communication monitoring system intervenes in the target user's communication application terminal, monitors the target user's communication location data in real time, and issues intervention alerts.

[0010] Although existing technologies involve communication activities similar to location sharing, the location data displayed on the device during autonomous movement is inaccurate and suffers from high latency due to communication signals, network issues, and other factors. Therefore, the system intervention described in this application can effectively remind users of the direction of travel, avoiding high error rates caused by network anomalies. Furthermore, this application is applicable to situations where the user is at a short distance and the surrounding environment is complex, resulting in inaccurate location transmission and making it impossible to effectively transmit communication content via voice, text, or images.

[0011] Furthermore, step S1 analyzes the communication transmission data of the communication transmission protocol connection and outputs the communication target characteristics, including the following analysis steps:

[0012] Data features are extracted from the communication transmission data. Data features refer to the characteristic representation of the transmitted data. Data features include text features, numerical features, image features, link features, and video / talk features. Link features include location links and program links. Video / talk features refer to the user sending or making video or voice calls through the communication application. The communication transmission data corresponding to the highest transmission frequency of data features is identified as high-density communication data. The first high-density communication data is taken as the starting node, and the process continues until the user's communication transmission data corresponds to a video / talk feature, which is taken as the ending node. Using high-density communication data as the starting node and video / talk features as the ending node is intended to limit the range of data transmitted by the user based on the communication application. Furthermore, video / talk features serve as a preparatory signal for the communication monitoring system in this application to intervene.

[0013] When the data features corresponding to the start node and the end node are the same, obtain the number of types of other data features in the communication transmission data excluding the start node and the end node; when the number of other data features is less than or equal to the threshold and the data features are regular features, output the communication target feature as the video feature.

[0014] When the data features corresponding to the start node and the end node are different, or when the data features corresponding to the start node and the end node are the same but the number of other data feature types is greater than the threshold for the number of types and the data feature is a variant feature, the data features corresponding to the communication transmission data are extracted in order and sorted to generate a feature set sequence.

[0015] Obtain the feature set sequence, divide the feature set sequence into two parts with the first variant feature as the boundary. The set of data features before the first variant feature in the feature set sequence constitutes the first feature set, and the set of data features after the first variant feature in the feature set sequence and including the variant feature constitutes the second feature set. Obtain the number of types n1 and the total number N1 of the regular features in the first feature set, and the number of types n2 and the total number N2 of the variant features in the second feature set;

[0016] If n1 > n2 and N1 > N2; output the communication target feature as the variant feature;

[0017] This situation indicates that the trend change in the feature set sequence is from regular features to variant features, and analyzing the quantitative relationship between regular features and variant features can reflect the importance of variant features from the side; the greater the difference between n1 and n2 and between N1 and N2, the more it indicates that the purpose of communication data transmission is reflected in the variant features;

[0018] If the above situation is not satisfied, output the communication target feature as the data feature corresponding to the high-density communication data.

[0019] Furthermore, the regular features and variant features include the following analysis steps:

[0020] When the visual call feature corresponds to a video or voice call, directly output it as a variant feature;

[0021] Obtain the storage capacity c and transmission duration t corresponding to the communication application end when the data features other than the visual call feature corresponding to a video or voice call are transmitted. Calculate the communication index w of the data features, w = a1 * c / c0 + a2 * t / t0; where c0 represents the average storage capacity of the communication transmission data corresponding to the total data features, t0 represents the average transmission rate of the communication transmission data corresponding to the total data features; a1 represents the reference coefficient corresponding to the storage capacity, a2 represents the reference coefficient corresponding to the transmission rate, 0 < a1 < 1, 0 < a2 < 1, a1 + a2 = 1;

[0022] Set the communication index threshold w0,

[0023] When w ≥ w0, output the data feature as a variant feature;

[0024] When w < w0, output the data feature as a regular feature.

[0025] Furthermore, step S2 includes the following analysis steps:

[0026] Obtain the communication transmission data content corresponding to the communication target feature as the target content; when there is location data in the target content, output the communication transmission data as the communication data to be analyzed; when there is no location data in the target content, output that there is no association relationship between the communication target feature and the communication location data;

[0027] The rate of change between the target content and the communication location data of the communication data to be analyzed is obtained; the rate of change refers to the relationship between the communication location data as the starting position from the moment the communication target characteristics are obtained and the monitoring distance as the location data corresponding to the target content.

[0028] When the monitoring distance decreases within the monitoring period, the output communication target characteristics and communication location data are correlated; otherwise, no correlation exists.

[0029] Furthermore, step S3 includes the following analysis steps:

[0030] To obtain the channel bandwidth B, the average power S of the transmitted signal within the channel, and the Gaussian noise power N within the channel of the user's communication transmission network, the formula is:

[0031] C = B * Log2(1 + S / N)

[0032] Calculate the maximum information transmission rate C under the communication transmission network where the user is located;

[0033] Obtain the maximum information transmission rate of different users connected by the communication transmission protocol, and sort the users from largest to smallest according to the maximum information transmission rate; output the communication user ranked first as the target intervention user.

[0034] The purpose of analyzing the target user is to determine whether the user's communication network is stable, secure, and efficient before the system intervenes. Since the data transmitted by the system also needs to occupy the channel, users with better and more secure communication status are more suitable for system intervention and can avoid communication anomalies.

[0035] The intelligent communication monitoring system includes a communication monitoring system construction module, a communication target feature analysis module, a correlation determination module, a target intervention user evaluation module, and an intervention reminder module.

[0036] The communication monitoring system construction module is used to monitor communication application terminals that use servers as relay stations and communication transmission protocols as bridges, and to build a communication monitoring system with users connected by communication transmission protocols and communication data as the main monitoring subjects;

[0037] The communication target feature analysis module is used to analyze the communication transmission data of the user after obtaining the user's monitoring permission and output the communication target features.

[0038] The correlation determination module is used to determine whether there is a correlation between the communication target features and the communication location data based on the communication target features.

[0039] The target intervention user evaluation module is used to select the optimal secure communication environment and determine the communication users corresponding to the optimal secure communication environment as the target intervention users.

[0040] The intervention alert module is used to monitor the communication location data of the target intervention user in real time and issue intervention alerts.

[0041] Furthermore, the communication target feature analysis module includes a data feature extraction unit, a communication node output unit, and a feature judgment unit;

[0042] The data feature extraction unit is used to extract data features from communication transmission data;

[0043] The communication node output unit is used to determine the starting node based on the transmission frequency of data characteristics, and to use video call characteristics as the ending node.

[0044] The feature judgment unit is used to analyze whether the data features of the starting node and the ending node are the same, and outputs the data features to which the communication target feature belongs based on the number of categories.

[0045] Furthermore, the correlation determination module includes a target content extraction unit, a communication data determination unit, a rate of change analysis unit, and a correlation output unit;

[0046] The target content extraction unit is used to obtain the communication transmission data content corresponding to the communication target features as the target content;

[0047] The communication data to be analyzed determination unit is used to output communication transmission data as communication data to be analyzed when location data exists in the target content;

[0048] The rate of change analysis unit is used to analyze the rate of change between the target content and the communication location data of the communication data to be analyzed;

[0049] The correlation output unit is used to output the correlation between the output results of the unit and the output results of the rate of change analysis unit based on the communication data to be analyzed.

[0050] Furthermore, the target intervention user evaluation module includes a channel data acquisition unit, a maximum information transmission rate calculation unit, and a user ranking extraction unit;

[0051] The channel data acquisition unit is used to acquire the channel bandwidth, the average power of the signal transmitted in the channel, and the Gaussian noise power in the channel of the communication transmission network where the user is located under the communication transmission protocol connection.

[0052] The maximum information transmission rate calculation unit is used to calculate the maximum information transmission rate under the communication transmission network where the user is located.

[0053] The user sorting and extraction unit sorts users from largest to smallest according to their maximum information transmission rate; the user ranked first in the sorting is the target intervention user.

[0054] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: The present invention monitors the communication application terminals with servers as relay stations and communication transmission protocols as bridges, and constructs a communication supervision system with users connected by communication transmission protocols and communication data as the monitoring subjects. It obtains the communication purpose of both parties in the process of communication behavior. When there is a correlation between the communication purpose and location data, the communication supervision system intervenes to intelligently control the user's communication. In addition, the conditions and characteristics of the communication scenarios applied in this application are diverse, and when the system intervenes, it performs a security assessment of the user's communication network status to select a suitable intervention channel, thereby realizing a safe and intelligent communication supervision system. Attached Figure Description

[0055] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0056] Figure 1 This is a schematic diagram of the structure of a big data-based intelligent communication security monitoring system according to the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] Please see Figure 1 This invention provides a technical solution: a big data-based intelligent communication security supervision method, comprising the following analysis steps:

[0059] Step S1: Monitor the communication application terminals that use servers as relay stations and communication transmission protocols as bridges, and build a communication monitoring system with users connected by communication transmission protocols and communication data as the main monitoring subjects. The communication data includes communication transmission data, communication location data, and communication environment data. When a user generates communication data, the communication monitoring system requests monitoring permissions. After obtaining the user's monitoring permissions, it analyzes the communication transmission data of the user connected by the communication transmission protocol and outputs the communication target characteristics.

[0060] Step S2: Based on the characteristics of the communication target, determine whether there is a correlation between the characteristics of the communication target and the communication location data;

[0061] Step S3: When there is a correlation, the communication monitoring system obtains the communication environment data of the user connected by the communication transmission protocol, and selects the optimal secure communication environment to determine the communication user corresponding to the optimal secure communication environment as the target intervention user;

[0062] Step S4: The communication monitoring system intervenes in the target user's communication application terminal, monitors the target user's communication location data in real time, and issues intervention alerts.

[0063] Intervention alerts include, but are not limited to, voice alerts, SMS alerts, and dynamic image alerts. Intervention alerts guided by communication target characteristics refer to the communication monitoring system obtaining the location data of another user connected to the target intervention user via a communication transmission protocol when a correlation is found between the communication target characteristics and communication location data, and providing real-time intervention alerts based on relative location. For example, if the real-time location of the target intervention user is location 1 and the location data of the other user is location 2, feasible routes can be planned for locations 1 and 2 based on big data, and the user can be alerted in real-time to the direction of travel. Alternatively, the two users can determine a location 3, and the system can plan their route accordingly.

[0064] Although existing technologies involve communication activities similar to location sharing, the location data displayed on the device during autonomous movement is inaccurate and suffers from high latency due to communication signals, network issues, and other factors. Therefore, the system intervention described in this application can effectively remind users of the direction of travel, avoiding high error rates caused by network anomalies. Furthermore, this application is applicable to situations where the user is at a short distance and the surrounding environment is complex, resulting in inaccurate location transmission and making it impossible to effectively transmit communication content via voice, text, or images.

[0065] Step S1 analyzes the communication transmission data of the communication transmission protocol connection and outputs the communication target characteristics, including the following analysis steps:

[0066] Data features are extracted from the communication transmission data. Data features refer to the characteristic representation of the transmitted data. Data features include text features, numerical features, image features, link features, and video / talk features. Link features include location links and program links. Video / talk features refer to the user sending or making video or voice calls through the communication application. The communication transmission data corresponding to the highest transmission frequency of data features is identified as high-density communication data. The first high-density communication data is taken as the starting node, and the process continues until the user's communication transmission data corresponds to a video / talk feature, which is taken as the ending node. Using high-density communication data as the starting node and video / talk features as the ending node is intended to limit the range of data transmitted by the user based on the communication application. Furthermore, video / talk features serve as a preparatory signal for the communication monitoring system in this application to intervene.

[0067] When the data features corresponding to the start node and the end node are the same, obtain the number of types of other data features in the communication transmission data excluding the start node and the end node; when the number of other data features is less than or equal to the threshold and the data features are regular features, output the communication target feature as the video feature.

[0068] When the data features corresponding to the start node and the end node are different, or when the data features corresponding to the start node and the end node are the same but the number of other data feature types is greater than the threshold for the number of types and the data feature is a variant feature, the data features corresponding to the communication transmission data are extracted in order and sorted to generate a feature set sequence.

[0069] The feature set sequence is divided into two parts with the first variant feature as the boundary. The set of data features before the first variant feature in the feature set sequence is the first feature set, and the set of data features after the first variant feature and including the variant feature is the second feature set. The number of types of regular features n1 and the total number N1 in the first feature set are obtained, as well as the number of types of variant features n2 and the total number N2 in the second feature set.

[0070] If n1>n2 and N1>N2, the output communication target feature is a variant feature.

[0071] This situation indicates that the trend change in the feature set sequence is a transformation from regular features to variant features, and analyzing the quantitative relationship between regular features and variant features can indirectly reflect the importance of variant features; the greater the difference between n1 and n2 and between N1 and N2, the more it indicates that the purpose of communication data transmission is reflected in the variant features.

[0072] If the above conditions are not met, the output communication target feature is the data feature corresponding to the high-density communication data.

[0073] The analysis steps for conventional and variant features are as follows:

[0074] When the visual call feature corresponds to a video or voice call, it is directly output as a variant feature;

[0075] Obtain the data features other than when the visual call feature corresponds to a video or voice call. When performing communication transmission, the storage capacity c and transmission duration t corresponding to the communication application end exist. Calculate the communication index w of the data features, w = a1*c / c0 + a2*t / t0; where c0 represents the average storage capacity of the communication transmission data corresponding to the total data features, and t0 represents the average transmission rate of the communication transmission data corresponding to the total data features; a1 represents the reference coefficient corresponding to the storage capacity, a2 represents the reference coefficient corresponding to the transmission rate, 0 < a1 < 1, 0 < a2 < 1, a1 + a2 = 1;

[0076] Set the communication index threshold w0,

[0077] When w ≥ w0, output the data feature as a variant feature;

[0078] When w < w0, output the data feature as a normal feature.

[0079] As shown in the embodiment: In practical applications, the storage capacity occupied by one hundred Chinese characters is two hundred bytes, while an image with a size of 3cm * 3cm occupies far more than two hundred bytes of storage capacity during communication transmission. Therefore, in this application when setting the communication index threshold, generally, data features such as text features and digital features are classified as normal features, and image features, link features, and visual call features are classified as variant features.

[0080] Step S2 includes the following analysis steps:

[0081] Obtain the communication transmission data content corresponding to the communication target feature as the target content; when there is location data in the target content, output the communication transmission data as the communication data to be analyzed; when there is no location data in the target content, output that there is no association relationship between the communication target feature and the communication location data;

[0082] Obtain the change rate of the target content of the communication data to be analyzed and the communication location data; the change rate refers to the change relationship when the communication location data starting from the moment of obtaining the communication target feature is used as the starting position to the position data corresponding to the target content as the monitoring distance;

[0083] When there is a situation where the monitoring distance decreases during the monitoring period, output that there is an association relationship between the communication target feature and the communication location data, otherwise there is no association relationship.

[0084] As shown in the example: if the communication transmission data content corresponding to the communication target feature is image data, then the target content is image data. To determine whether location data exists in the image data, big data analysis is used to see if buildings and landmarks that can reflect location information are present in the image. If it is a human figure, it cannot be reflected. When location data exists, the spatial distance between the current user's communication location and the location information is further analyzed. If the user's spatial distance is constantly decreasing, it means that the user is moving towards the target location. Then it is determined that the purpose of outputting the communication transmission data is to go to that location. If it is location data, the location data is obtained more directly. If it is voice data, keyword information is obtained.

[0085] Step S3 includes the following analysis steps:

[0086] To obtain the channel bandwidth B, the average power S of the transmitted signal within the channel, and the Gaussian noise power N within the channel of the user's communication transmission network, the formula is:

[0087] C = B * Log2(1 + S / N)

[0088] Calculate the maximum information transmission rate C under the communication transmission network where the user is located;

[0089] Obtain the maximum information transmission rate of different users connected by the communication transmission protocol, and sort the users from largest to smallest according to the maximum information transmission rate; output the communication user ranked first as the target intervention user.

[0090] The purpose of analyzing the target user is to determine whether the user's communication network is stable, secure, and efficient before the system intervenes. Since the data transmitted by the system also needs to occupy the channel, users with better and more secure communication status are more suitable for system intervention and can avoid communication anomalies.

[0091] The intelligent communication monitoring system includes a communication monitoring system construction module, a communication target feature analysis module, a correlation determination module, a target intervention user evaluation module, and an intervention reminder module.

[0092] The communication monitoring system construction module is used to monitor communication application terminals that use servers as relay stations and communication transmission protocols as bridges, and to build a communication monitoring system with users connected by communication transmission protocols and communication data as the main monitoring subjects;

[0093] The communication target feature analysis module is used to analyze the communication transmission data of the user after obtaining the user's monitoring permission and output the communication target features.

[0094] The correlation determination module is used to determine whether there is a correlation between the communication target features and the communication location data based on the communication target features.

[0095] The target intervention user evaluation module is used to select the optimal secure communication environment and determine the communication users corresponding to the optimal secure communication environment as the target intervention users.

[0096] The intervention alert module is used to monitor the communication location data of the target intervention user in real time and issue intervention alerts.

[0097] The communication target feature analysis module includes a data feature extraction unit, a communication node output unit, and a feature judgment unit;

[0098] The data feature extraction unit is used to extract data features from communication transmission data;

[0099] The communication node output unit is used to determine the starting node based on the transmission frequency of data characteristics, and to use video call characteristics as the ending node.

[0100] The feature judgment unit is used to analyze whether the data features of the starting node and the ending node are the same, and outputs the data features to which the communication target feature belongs based on the number of categories.

[0101] The correlation determination module includes a target content extraction unit, a communication data determination unit, a rate of change analysis unit, and a correlation output unit;

[0102] The target content extraction unit is used to obtain the communication transmission data content corresponding to the communication target features as the target content;

[0103] The communication data to be analyzed determination unit is used to output communication transmission data as communication data to be analyzed when location data exists in the target content;

[0104] The rate of change analysis unit is used to analyze the rate of change between the target content and the communication location data of the communication data to be analyzed;

[0105] The correlation output unit is used to output the correlation between the output results of the unit and the output results of the rate of change analysis unit based on the communication data to be analyzed.

[0106] The target intervention user evaluation module includes a channel data acquisition unit, a maximum information transmission rate calculation unit, and a user ranking extraction unit;

[0107] The channel data acquisition unit is used to acquire the channel bandwidth, the average power of the signal transmitted in the channel, and the Gaussian noise power in the channel of the communication transmission network where the user is located under the communication transmission protocol connection.

[0108] The maximum information transmission rate calculation unit is used to calculate the maximum information transmission rate under the communication transmission network where the user is located.

[0109] The user sorting and extraction unit sorts users from largest to smallest according to their maximum information transmission rate; the user ranked first in the sorting is the target intervention user.

[0110] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0111] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A communication intelligent security supervision method based on big data, characterized in that, The analysis includes the following steps: Step S1: Monitor the communication application terminals that use servers as relay stations and communication transmission protocols as bridges, and construct a communication monitoring system with users connected by communication transmission protocols and communication data as the main monitoring subjects. The communication data includes communication transmission data, communication location data, and communication environment data. When a user generates communication data, the communication monitoring system requests monitoring permissions. After obtaining the user's monitoring permissions, it analyzes the communication transmission data of the user connected by the communication transmission protocol and outputs the communication target characteristics. Step S1, which analyzes the communication transmission data of the communication transmission protocol connection and outputs the communication target characteristics, includes the following analysis steps: Extracting data features from communication transmission data, wherein the data features refer to the characteristic representation of the transmission data; the data features include text features, number features, image features, link features, and video features; The link features include location links and program links. The video call feature refers to the user sending or making a call through the communication application terminal. The communication transmission data corresponding to the highest transmission frequency of the data feature is high-density communication data. The first high-density communication data is the starting node, and the process continues until the data feature corresponding to the user's communication transmission data is the video call feature, which is the ending node. When the data features corresponding to the start node and the end node are the same, obtain the number of types of other data features in the communication transmission data excluding the start node and the end node; when the number of other data features is less than or equal to the threshold of the number of types and the data features are regular features, output the communication target feature as a video feature. When the data features corresponding to the start node and the end node are different, or when the data features corresponding to the start node and the end node are the same but the number of other data feature types is greater than the threshold for the number of types and the data feature is a variant feature, the data features corresponding to the communication transmission data are extracted in order and sorted to generate a feature set sequence. The feature set sequence is divided into two parts with the first variant feature as the boundary. The set of data features before the first variant feature in the feature set sequence is the first feature set, and the set of data features after the first variant feature and including the variant feature in the feature set sequence is the second feature set. The number of types n1 and the total number N1 of regular features in the first feature set are obtained, as well as the number of types n2 and the total number N2 of variant features in the second feature set. If n1>n2 and N1>N2, the output communication target feature is a variant feature. If the above conditions are not met, the output communication target feature is the data feature corresponding to the high-density communication data; Step S2: Based on the communication target characteristics, determine whether there is a correlation between the communication target characteristics and the communication location data; Step S3: When there is a correlation, the communication monitoring system obtains the communication environment data of the user connected by the communication transmission protocol, and selects the optimal secure communication environment to determine the communication user corresponding to the optimal secure communication environment as the target intervention user; Step S4: The communication supervision system intervenes in the communication application end of the target intervened user, monitors the communication location data of the target intervened user in real time, and gives an intervention reminder.

2. The communication intelligent security supervision method based on big data according to claim 1, characterized in that: The above-mentioned conventional features and variant features include the following analysis steps: When the visual call feature corresponds to a video or voice call, it is directly output as a variant feature; Obtain the storage capacity c and transmission duration t corresponding to the communication application end when the data features other than the visual call feature correspond to a video or voice call during communication transmission, and calculate the communication index w of the data features, where w = a1*c / c0 + a2*t / t0; here, c0 represents the average storage capacity of the communication transmission data corresponding to the total data features, t0 represents the average transmission rate of the communication transmission data corresponding to the total data features; a1 represents the reference coefficient corresponding to the storage capacity, a2 represents the reference coefficient corresponding to the transmission rate, 0 < a1 < 1, 0 < a2 < 1, and a1 + a2 = 1; Set the communication index threshold w0, When w ≥ w0, output the data feature as a variant feature; When w < w0, output the data feature as a conventional feature.

3. The communication intelligent security supervision method based on big data according to claim 2, characterized in that: The above-mentioned step S2 includes the following analysis steps: Obtain the communication transmission data content corresponding to the communication target feature as the target content; when there is location data in the target content, output the communication transmission data as the communication data to be analyzed; when there is no location data in the target content, output that there is no association between the communication target feature and the communication location data; Obtain the change rate of the target content of the communication data to be analyzed and the communication location data; the change rate refers to the change relationship when the communication location data starting from the moment when the communication target feature is obtained is used as the starting position and the position data corresponding to the target content is used as the monitoring distance; When there is a situation where the monitoring distance decreases during the monitoring period, output that there is an association between the communication target feature and the communication location data, otherwise there is no association.

4. The communication intelligent security supervision method based on big data according to claim 3, characterized in that: The above-mentioned step S3 includes the following analysis steps: Obtain the channel bandwidth B, the average power S of the signal transmitted in the channel, and the Gaussian noise power N inside the channel under the communication transmission network connected by the communication transmission protocol of the user, and use the formula: C = B * Log2(1 + S / N) Calculate the maximum information transfer rate C under the communication transmission network where the user is located; Obtain the maximum information transfer rates of different users connected by the communication transmission protocol, and sort the users in descending order according to the values of the maximum information transfer rates; output the communication user ranked first as the target intervened user.

5. A communication intelligent security monitoring system applying any one of the big data-based communication intelligent security monitoring methods according to claims 1-4, characterized in that, It includes a communication supervision system construction module, a communication target feature analysis module, an association relationship determination module, a target intervened user evaluation module, and an intervention reminder module; The communication supervision system construction module is used to monitor the communication application end with the server as the transfer station and the communication transmission protocol as the bridge, and construct a communication supervision system with the users connected by the communication transmission protocol and the communication data as the monitoring objects; The communication target feature analysis module is used to analyze the communication transmission data of the users connected by the communication transmission protocol after obtaining the user monitoring permission and output the communication target features; The association relationship determination module is used to judge whether there is an association between the communication target feature and the communication location data based on the communication target feature; The target intervention user evaluation module is used to select the optimal secure communication environment and determine the communication user corresponding to the optimal secure communication environment as the target intervention user. The intervention alert module is used to monitor the communication location data of the target intervention user in real time and issue intervention alerts.

6. The intelligent communication monitoring system according to claim 5, characterized in that: The communication target feature analysis module includes a data feature extraction unit, a communication node output unit, and a feature judgment unit; The data feature extraction unit is used to extract data features of communication transmission data; The communication node output unit is used to determine the starting node based on the transmission frequency of data characteristics, and to use video features as the ending node. The feature judgment unit is used to analyze whether the data features of the starting node and the ending node are the same, and outputs the data features to which the communication target feature belongs based on the number of categories.

7. The intelligent communication monitoring system according to claim 6, characterized in that: The correlation determination module includes a target content extraction unit, a communication data determination unit to be analyzed unit, a rate of change analysis unit, and a correlation output unit. The target content extraction unit is used to obtain the communication transmission data content corresponding to the communication target features as the target content; The communication data to be analyzed determination unit is used to output communication transmission data as communication data to be analyzed when there is location data in the target content; The rate of change analysis unit is used to analyze the rate of change between the target content and the communication location data of the communication data to be analyzed. The correlation output unit is used to output the correlation relationship based on the output results of the determination unit and the output results of the rate of change analysis unit of the communication data to be analyzed.

8. The intelligent communication monitoring system according to claim 7, characterized in that: The target intervention user evaluation module includes a channel data acquisition unit, a maximum information transmission rate calculation unit, and a user ranking extraction unit. The channel data acquisition unit is used to acquire the channel bandwidth, the average power of the signal transmitted in the channel, and the Gaussian noise power in the channel under the communication transmission network where the user is connected by the communication transmission protocol. The maximum information transmission rate calculation unit is used to calculate the maximum information transmission rate under the communication transmission network where the user is located. The user sorting and extraction unit is used to sort users from largest to smallest according to the maximum information transmission rate; the communication user ranked first is output as the target intervention user.

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