WO2023138098A1

WO2023138098A1 - User group attribute analysis system and method based on online network

Info

Publication number: WO2023138098A1
Application number: PCT/CN2022/122430
Authority: WO
Inventors: 刘长征; 张荣华; 袁李萌子; 邵闻珠; 刘雅辉; 刘昭
Original assignee: 石河子大学
Priority date: 2022-01-20
Filing date: 2022-09-29
Publication date: 2023-07-27
Also published as: CN114372204A; CN114372204B

Abstract

The present invention relates to the technical field of network big data capture, and in particular to a user group attribute analysis system and method based on an online network. The system comprises: a system terminal which is a master control end of the system and is used for issuing an execution command for each lower-level module to execute; an implanting module used for implanting the system to a mobile device used by a user; a compatible module used for obtaining configuration data of the mobile device into which the system is implanted; and a retrieving module used for retrieving stored data in a storage space of the mobile device. The present invention provides a user group attribute analysis system based on an online network. The system can supervise, to a certain extent, electronic devices which are used by people in a student period and can be networked, and the system is hidden in the electronic devices and cannot be found, so that the conflict psychology of the students is avoided, the privacy of the students is protected, parents and teachers are assisted, the students can be cared and taught more appropriately and can be guided correctly, and healthy growth of the students can be guaranteed.

Description

System and method for user group attribute analysis based on online network

This application claims the priority of the Chinese patent application with the application number 202210067593.8 and the invention title "Online Network-Based User Group Attribute Analysis System and Method" submitted to the China Patent Office on January 20, 2022, the entire contents of which are incorporated in this application by reference.

technical field

The invention relates to the technical field of network big data capture, in particular to an online network-based user group attribute analysis system and method.

Background technique

With the development and progress of society, the use of electronic devices has gradually become younger. Except for preschool education, children, adolescents, and young people are basically equipped with mobile phones. However, mobile phones and other related electronic devices can collect a large amount of data from the Internet when they are connected to the Internet. Many of them contain some unhealthy and improper ideas. .

Nowadays, parents and teachers can give limited guidance to students. If students are in a rebellious period, the key to the problem cannot be solved by using network restrictions. How to guide students to establish a correct outlook on life and values in the network is a major problem in today's education.

Contents of the invention

Technical issues resolved

Aiming at the above-mentioned shortcomings in the prior art, the present invention provides an online network-based user group attribute analysis system and method, which solves the problem that the current technology cannot better guide students' online behaviors, causing students to have wrong outlooks on life and values under the influence of unfavorable physical and mental health data in network information due to their contact with the Internet.

Technical solutions

To achieve the above object, the present invention is achieved through the following technical solutions:

In the first aspect, an online network-based user group attribute analysis system includes:

The system terminal is the general control terminal of the system, which is used to issue execution commands for execution by the lower-level modules;

An implant module, used to implant the system on the mobile device used by the user;

Compatible module, used to obtain configuration data of mobile devices implanted in the system;

A retrieval module, configured to retrieve stored data in the storage space of the mobile device;

The evaluation module is used to evaluate whether there is any abnormality in the content of the stored data in the retrieval module, and the proportion of abnormal data;

A judging module, used for judging the attributes of the system end users;

A coordination module, configured to receive the user attributes determined by the determination module, and coordinate the evaluation indicators of the evaluation module according to the user attributes;

The reporting module is used to send the coordination results of the coordination module to the superior system terminal and the control terminal; the system terminal is a post-setting report, and selectively reports to the system terminal after the control terminal receives the report result.

Furthermore, the wireless network is used to establish a security system in the implanted module, including:

The stealth module is used to hide the system in the mobile device loaded with the system;

The secret key source library is used to randomly generate time-limited secret keys in real time for the use of the control terminal, and log in to the system to control the system terminal;

The authorization module is used to authorize the security system to obtain the usage record of the main system;

The keyword library is used to store abnormal words for statistics after comparison by the statistics module;

The statistical module is used to count the number of targets matching the keyword library in the usage records of the main system acquired by the authorization module.

Furthermore, the retrieval module establishes a connection with the statistics module through a wireless network for data transmission, and synchronously obtains the target quantity in the usage records of the main system obtained in the statistics module that matches the keyword library when the retrieval module is running, and further participates in the operation of the evaluation module.

Furthermore, the evaluation module and the judgment module are connected in parallel to the main control module through a medium, and are used to replace the evaluation module and the judgment module for execution, and the main control system modifies or matches the end user attributes of the system.

Furthermore, the first to fourth grades of evaluation indicators in the evaluation module correspond to: primary school, junior high school, high school, university and above.

In the second aspect, an online network-based user group attribute analysis method includes the following steps:

Step1: Implant the system in the mobile device of the client, so that the system enters a stealth state and cannot be retrieved by the system program in the mobile device;

Step2: Set up the recording program, connect the trusted device to connect to the stealth system in the client mobile device;

Step3: Set the abnormal behavior capture trigger conditions, match the abnormal behavior capture trigger conditions with the level of the mobile device client, and actively coordinate the compatibility between the trigger conditions and the mobile device client level after logging in on the trusted device;

Step4: Trust the device side to periodically use the secret key to verify the identity and log in to the control side to retrieve the relevant report files of the user side in the database for attribute analysis and evaluation;

Step5: The trusted device operation terminal establishes a communication connection with the user terminal to guide it according to the attribute analysis and evaluation results of the relevant report file of the corresponding user terminal.

Furthermore, in Step 2, the trusted device connects to the hidden system in the mobile device through the public key of the local wireless network. When the trusted device establishes a connection with the user's mobile device, it uses the secret key to verify the identity of the operator. The hidden system in the user's mobile device includes a recording program. When the user's mobile device and the trusted device are in the same local area network, it automatically corrects and establishes a data transmission channel. After the data transmission channel is established, the user's mobile device transmits the recording program record data to the trusted device.

Furthermore, the step Step2 includes a recording program, including the following steps:

Step21: Analyze the attributes of the user terminal, match the abnormal behavior capture authority of the mobile device of the user terminal, and capture the operation behavior of the user terminal on its mobile device that meets the characteristics of abnormal behavior according to the abnormal behavior capture authority matched by the mobile device of the user terminal;

Step22: Summarize the abnormal behavior of the mobile device on the client side to generate a report file, compare the selectivity of the report file with the abnormal behavior capture permission, and send it to the trusted device for waiting;

Step23: Create a database, and after the trusted device confirms the report file, transfer the report file to the database to create a root directory storage.

Furthermore, step Step5 includes a sub-step Step51: check the abnormal behavior captured in the report file, retrieve the network IP address related to the abnormal behavior for further analysis, and perform adaptive processing on the content of the network IP address related to the retrieved abnormal behavior;

Among them, the adaptive processing plan for the network IP address content related to abnormal behavior includes: reporting, banning, jumping and synchronous feedback.

Furthermore, in Step 2, when the user of the trusted device is online, the abnormal behavior prediction function formula is selectively used to calculate the next occurrence probability of abnormal behavior of the mobile device of the user, the formula is as follows:

In the formula: P(B _i ), P(B _j ) are the basic probability;

P(A|B _i ) is the hit rate;

P(A|B _j ) is the false alarm rate.

Beneficial effect

Compared with the known public technology, the technical solution provided by the invention has the following beneficial effects:

1. The present invention provides an online network user group attribute analysis system. The system is aimed at students who are in the student period. The system can supervise the electronic devices that can be connected to the Internet to a certain extent. The system can be hidden in the electronic devices without being discovered, and the users can be supervised within the scope of authority, thereby avoiding the resistance of students. At the same time, it protects the privacy of students, assists parents and teachers, and can provide more appropriate care and guidance for students, as well as correct guidance on the road of life, to ensure their healthy growth.

2. The present invention can be adapted according to the stage of the student's goal, so that the privacy of the student is further protected during use, and the use is relatively safe, and parents or teachers can only get the final report result. While respecting the student, it ensures that the student's improper behavior is caught, so that the parent or teacher can guide the student in a more timely manner.

3. In the process of using the present invention, the trusted device-side control user can be in charge, and the actual inspection is carried out according to the data reported by the system, so as to ensure that even if there is an error in the data obtained by the system, the trusted device-side control user can detect even if there is an error, so as to make more accurate judgments and actual actions.

4. The present invention provides an online network user group attribute analysis method. Through this method, parents of students can understand their children better, and teachers can understand their students better, so as to make some predictive and reasonable guiding interventions, so that students can proactively reject the next bad information in the network that will occur next time, so as to achieve the purpose of establishing a correct outlook on life and values more independently.

Instructions attached

In order to illustrate the present invention or the technical solution in the prior art more clearly, the accompanying drawings that need to be used in the description of the embodiments or the prior art will be briefly introduced below. Apparently, the drawings in the following description are only some embodiments of the present invention, and those skilled in the art can obtain other drawings according to these drawings without creative efforts.

Fig. 1 is the structural representation of the user group attribute analysis system based on online network;

Fig. 2 is a schematic flow chart of a user group attribute analysis method based on an online network;

The labels in the figure respectively represent: 1. system terminal; 11. control terminal; 2. implant module; 21. security system; 211. stealth module; 212. secret key source library; 213. authorization module; 214. keyword library; 215. statistics module;

Detailed ways

In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Apparently, the described embodiments are some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

The present invention will be further described below in conjunction with embodiment.

Example 1

The online network-based user group attribute analysis system of the present embodiment, as shown in Figure 1, includes:

The system terminal 1 is the general control terminal of the system, and is used to issue execution commands for execution by the lower-level modules.

The implant module 2 is used for implanting the system in the mobile device used by the user.

Compatible module 3 is used to obtain configuration data of mobile devices implanted in the system.

The retrieval module 4 is configured to retrieve the stored data in the storage space of the mobile device.

The evaluation module 5 is used to evaluate whether there is any abnormality in the content of the data stored in the retrieval module 4, and the proportion of abnormal data.

The determination module 6 is used to determine the user attribute of the system terminal 1 .

The coordination module 7 is configured to receive the user attributes determined by the determination module 6, and coordinate the evaluation indicators of the evaluation module 5 according to the user attributes.

The reporting module 8 is used to report the coordination results of the coordination module 7 to the superior system terminal 1 and the control terminal 11; wherein the system terminal 1 is a post-setting report, and selectively reports to the system terminal 1 after the control terminal 11 receives the report result.

When used in this embodiment, the system is installed in the mobile device used by the client through the implant module 2, and the configuration data of the mobile device implanted in the system can be obtained through the compatible module 3, and the existing content in the mobile device is obtained, and then the existing stored data content is retrieved through the retrieval module 4, so that the data is evaluated by the evaluation module 5, and whether there is abnormality in the stored data content in the retrieval module 4, and the proportion of abnormal data, so that the attribute of the user of the system terminal 1 and the user terminal can be determined through the determination module 6.

Further, when the target served by the system terminal 1 grows, the system can coordinate the evaluation index of the evaluation module 5 according to user attributes through the coordination module 7 .

In addition, the reporting module 8 can report the coordination result of the coordination module 7 to the superior system terminal 1 and the control terminal 11, so that the management user at the trusted end knows in real time whether there is any abnormal behavior in the process of operating the mobile device at the user end.

Example 2

In terms of specific implementation, as shown in Figure 1 in this embodiment, the implanted module 2 establishes a security system 21 with a wireless network, including:

The stealth module 211 is used to hide the system in the mobile device loaded with the system.

The key source library 212 is used to randomly generate a time-limited key in real time for use by the control terminal 11 , and the system terminal 1 is used to control the login system.

The authorization module 213 is configured to authorize the security system 21 to obtain the master system use record.

The keyword library 214 is used to store abnormal words for the statistics module 215 to perform comparison and statistics.

The statistical module 215 is configured to count the number of targets matched with the keyword database 214 in the master system usage records acquired by the authorization module 213 .

During the use of this embodiment, the stealth module 211 serves the main system so that the system can be hidden in the mobile device without being noticed. Every time the trusted device user needs to enter the system to view the data information in the system terminal 1 obtained and recorded in the system, he can randomly generate a time-limited key through the key source library 212 for the trusted device to perform identity verification and then enter the system.

At the same time, after entering the system, the keyword library 214 is used synchronously to compare with the data information captured in the system, and then the statistical module 215 is used to obtain statistical results, so as to assist and trust the device-side users to judge whether the system terminal 1 has abnormal behavior during the use of mobile devices, so as to take actions according to the actual situation to ensure that the users of the system terminal 1 use the network under a healthy, safe and stable network.

As shown in FIG. 1 , the retrieval module 4 establishes a connection with the statistical module 215 through a wireless network for data transmission. When the retrieval module 4 is running, it simultaneously obtains the target quantity that matches the keyword library 214 in the main system usage records obtained in the statistical module 215, and further participates in the operation of the evaluation module 5.

This setting can provide the evaluation module 5 with an accurate evaluation target, and assist the evaluation module 5 to make a more accurate judgment.

As shown in FIG. 1 , the evaluation module 5 and the determination module 6 are connected in parallel to the main control module 561 through a medium, and are used to replace the evaluation module 5 and the determination module 6 for execution. The main control system (ie, the main control module 561) modifies or matches the user attributes of the system terminal 1.

Through this setting, the trusted device side and the control terminal 11 can be used to control the system in two ways, so as to provide convenience for the control terminal 11 and enable the system to be used better.

As shown in Figure 1, the first to fourth grades of evaluation indicators in the evaluation module 5 correspond to: primary school, junior high school, high school, university and above.

Example 3

At the specific implementation level, on the basis of Embodiment 1, this embodiment further specifically explains the user group attribute analysis system of the online network in Embodiment 1 with reference to FIG. 1. As shown in FIG. 2, the user group attribute analysis method based on the online network includes the following steps:

Step1: Implant the system in the mobile device of the user end, so that the system enters a stealth state and cannot be retrieved by the system program in the mobile device.

Step2: Set up the recording program, connect the trusted device to connect to the stealth system in the client mobile device.

Step3: Set the abnormal behavior capture trigger conditions, match the abnormal behavior capture trigger conditions and the level of the mobile device client, and actively coordinate the compatibility between the trigger conditions and the mobile device client level after logging in on the trusted device.

Step4: Trust the device side to periodically use the secret key to verify the identity and log in to the control side to retrieve the relevant report files of the user side in the database for attribute analysis and evaluation.

Step5: The operation terminal of the trusted device establishes a communication connection with the user terminal to guide it according to the analysis and evaluation results of the relevant report file attributes of the corresponding user terminal.

As shown in Figure 2, in Step 2, the trusted device connects to the hidden system in the mobile device through the public key of the local wireless network. When the trusted device establishes a connection with the user's mobile device, it uses the secret key to verify the identity of the operator. The hidden system in the user's mobile device includes a recording program. When the user's mobile device and the trusted device are in the same local area network, it automatically corrects and establishes a data transmission channel. After the data transmission channel is established, the user's mobile device transmits the recording program record data to the trusted device.

As shown in Figure 2, the step Step2 includes a recording program, including the following steps:

Step21: Analyze the attributes of the user terminal, match the abnormal behavior capture authority of the user terminal mobile device, and capture the operation behavior that the user terminal uses on its mobile device that meets the characteristics of abnormal behavior according to the abnormal behavior capture authority matched by the user terminal mobile device.

Step22: Summarize the abnormal behavior of the mobile device on the client side to generate a report file, compare the selectivity of the report file with the abnormal behavior capture permission, and send it to the trusted device for waiting.

As shown in Figure 2, step Step5 includes sub-step Step51: check the abnormal behavior captured in the report file, retrieve the network IP address related to the abnormal behavior for further analysis, and perform adaptive processing on the content of the network IP address related to the retrieved abnormal behavior.

In addition, in Step 2, when the user of the trusted device is online, the abnormal behavior prediction function formula is selectively used to calculate the next abnormal behavior occurrence probability of the mobile device of the user, the formula is as follows:

In the formula: P(B _i ), P(B _j ) are the basic probability; P(A|B _i ) is the hit rate; P(A|B _j ) is the false alarm rate.

Through this formula, the user of the trusted device can perform further calculations to calculate the abnormal behavior that may occur in the next period of time when the mobile device of the user is used by the user, thereby assisting the user of the trusted device to conduct reasonable supervision on the users of the mobile device of the user, so as to guide the abnormal behavior before it occurs, so that the user of the mobile device of the user can obtain a better growth environment.

To sum up, the present invention provides an online network user group attribute analysis system. The system is aimed at students who are in the student period, and can supervise their electronic devices that can be connected to the Internet to a certain extent. The system can be hidden in electronic devices without being discovered, and supervise users within the scope of authority, thereby avoiding students' resistance, while protecting students' privacy, assisting parents and teachers, and providing more appropriate care and teaching for students, correct guidance on the road of life, and ensuring their healthy growth;

Moreover, the present invention can carry out adaptive allocation according to the stage of the student's goal, thereby further protecting the privacy of the students during use, and the use is relatively safe, and the parents or teachers can only get the final report result, while respecting the students, it ensures that the students' improper behaviors are caught, so that the parents or teachers can guide the students in a more timely manner; Discovery, so as to make more accurate judgments and practical actions.

Moreover, the present invention provides an online network user group attribute analysis method. Through this method, parents of students can better understand their children, and teachers can better understand their students, so as to make some predictable and reasonable guiding interventions, so that students can proactively reject the next bad information in the network that will occur next time, so as to achieve the purpose of establishing a correct outlook on life and values more independently.

The above embodiments are only used to illustrate the technical solutions of the present invention, not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements to some of the technical features; and these modifications or replacements will not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

The online network-based user group attribute analysis system is characterized in that it includes:

The system terminal (1) is the general control terminal of the system, which is used to issue execution commands for execution by the lower-level modules;

An implant module (2), used for implanting the system on the mobile device used by the user;

A compatible module (3), used to obtain the configuration data of the mobile device implanted in the system;

A retrieval module (4), configured to retrieve stored data in the storage space of the mobile device;

An evaluation module (5), configured to evaluate whether there is anomaly in the content of the stored data in the retrieval module (4), and the proportion of abnormal data;

A judging module (6), used for judging the user attributes of the system terminal (1);

A coordination module (7), configured to receive the user attributes determined by the determination module (6), and coordinate the evaluation indicators of the evaluation module (5) according to the user attributes;

The reporting module (8) is used to send the coordination result of the coordination module (7) to the superior system terminal (1) and the control terminal (11); wherein the system terminal (1) is a post-set report, and selectively reports to the system terminal (1) after the control terminal (11) receives the report result.
The user group attribute analysis system based on the online network according to claim 1, wherein, in the implanted module (2), a safety system (21) is set up with a wireless network, including:

Stealth module (211), used for the stealth system in the mobile device loaded with the system;

The secret key source library (212), which is used to randomly generate a time-limited secret key in real time for use by the control terminal (11), and the system terminal (1) is used to log in to the system for manipulation;

An authorization module (213), configured to authorize the security system (21) to obtain the use record of the main system;

The keyword library (214) is used to store abnormal words for the statistical module (215) to perform comparison and statistics;

A statistical module (215), configured to count the number of targets matched with the keyword library (214) in the master system usage records acquired by the authorization module (213).
The online network-based user group attribute analysis system according to claim 1, wherein the retrieval module (4) establishes a connection with the statistical module (215) through a wireless network to perform data transmission, and synchronously acquires the target quantity matched with the keyword library (214) in the main system usage record obtained in the statistical module (215) when the retrieval module (4) runs, and further participates in the operation of the evaluation module (5).
The online network-based user group attribute analysis system according to claim 1, wherein the evaluation module (5) and the judgment module (6) are connected in parallel to the main control module (561) through a medium, and are used to replace the evaluation module (5) and the judgment module (6) for execution, and the main control system modifies or matches the user attributes of the system terminal (1).
The online network-based user group attribute analysis system according to claim 1, characterized in that the first to fourth grades of evaluation indicators in the evaluation module (5) respectively correspond to: primary school, junior high school, high school, university and above.
The user group attribute analysis method based on online network, described method is the implementation method to the user group attribute analysis system of online network according to any one of claims 1-5, it is characterized in that, comprises the following steps:

Step1: Implant the system in the mobile device of the client, so that the system enters a stealth state and cannot be retrieved by the system program in the mobile device;

Step2: Set up the recording program, connect the trusted device to connect to the stealth system in the client mobile device;

Step3: Set the abnormal behavior capture trigger conditions, match the abnormal behavior capture trigger conditions and the level of the mobile device client, and actively coordinate the compatibility between the trigger conditions and the mobile device client level after logging in on the trusted device;

Step4: Trust the device side to periodically use the secret key to verify the identity and log in to the control side to retrieve the relevant report files of the user side in the database for attribute analysis and evaluation;

Step5: The trusted device operation terminal establishes a communication connection with the user terminal to guide it according to the attribute analysis and evaluation results of the relevant report file of the corresponding user terminal.
The user group attribute analysis method based on an online network according to claim 6, wherein in step Step2, the trusted device connects to the invisible system in the mobile device through the public key of the local wireless network. When the trusted device establishes a connection with the user's mobile device, the identity of the operator is verified using the secret key. The hidden system in the user's mobile device includes a recording program. When the user's mobile device and the trusted device are in the same local area network, it automatically corrects and establishes a data transmission channel. data.
The user group attribute analysis method based on online network according to claim 6, wherein the step Step2 includes a recording program, comprising the following steps:

Step21: Analyze the attributes of the user terminal, match the abnormal behavior capture authority of the mobile device of the user terminal, and capture the operation behavior of the user terminal on its mobile device that meets the characteristics of abnormal behavior according to the abnormal behavior capture authority matched by the mobile device of the user terminal;

Step22: Summarize the abnormal behavior of the mobile device on the client side to generate a report file, compare the selectivity of the report file with the abnormal behavior capture permission, and send it to the trusted device for waiting;

Step23: Create a database, and after the trusted device confirms the report file, transfer the report file to the database to create a root directory storage.
The online network-based user group attribute analysis method according to claim 6, characterized in that step Step5 includes substep Step51: check the abnormal behavior captured in the report file, retrieve the network IP address related to the abnormal behavior for further analysis, and perform adaptive processing on the content of the network IP address related to the retrieved abnormal behavior;

Among them, the adaptive processing plan for the network IP address content related to abnormal behavior includes: reporting, banning, jumping and synchronous feedback.
The user group attribute analysis method based on online network according to claim 6, characterized in that, in the step Step2, the trusted device end user is in an online state, and selectively uses the abnormal behavior prediction function formula to calculate the next abnormal behavior occurrence probability of the user end mobile device, and the formula is as follows:

In the formula: P(B i ), P(B j ) are the basic probability;

P(A|B i ) is the hit rate;

P(A|B j ) is the false alarm rate.