A network control system with a prediction function for continuous monitoring

Abstract

The present application relates to network security monitoring technical field, specifically, it relates to a kind of continuous monitoring network control system with prediction function.It includes behavior detection unit, speech monitoring unit, inertia analysis unit, behavior prediction unit and early warning control unit.In the present application, the information of special vocabulary speaker is determined by setting behavior detection unit, and it is set as the target of monitoring, and inertia analysis is carried out on the target of monitoring, the habit of the target of monitoring is obtained, and early warning is carried out according to the habit of speech, and the target of monitoring is warned after early warning, the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time, and the target of monitoring is prevented in time

Description

Technical Field

[0001] The present invention relates to the technical field of network security monitoring, in particular to a network control system with continuous monitoring and prediction function. Background Art

[0002] A network is composed of nodes and lines, representing many objects and their mutual connections. A network is a model abstracted from some practical problems of the same type. In the computer field, a network is a virtual platform for information transmission, reception, and sharing. It connects the information of various points, surfaces, and bodies together, thereby realizing the sharing of these resources.

[0003] However, because the Internet is virtual, the dissemination and expression of opinions on the Internet are too casual and cannot bring people the profound meaning of the opinions expressed. As a result, the Internet has become a place where some people can express themselves wantonly, and the wanton expression of opinions can cause harm to others and affect their normal lives. Summary of the Invention

[0004] The object of the present invention is to provide a network control system with continuous monitoring and prediction function to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides a continuous monitoring network control system with prediction function, comprising a behavior detection unit, a speech monitoring unit, an inertia analysis unit, a behavior prediction unit and an early warning control unit;

[0006] The behavior detection unit is used to search for some special words on the Internet and determine the monitoring target after determining the meaning of the special words;

[0007] The speech monitoring unit is used to monitor the speech behavior of the monitoring target determined by the behavior detection unit to obtain the normal behavior of the monitoring target;

[0008] The inertia analysis unit determines the inertia of the monitoring target based on the behavior normality of the speech monitoring unit and obtains the inertia steps of the monitoring target;

[0009] The behavior prediction unit is used to analyze the steps of the published speech according to the inertial steps of the monitoring target obtained by the inertia analysis unit, and predict the speech process of the monitoring target;

[0010] After determining the speech process of the monitored target, the early warning control unit issues early warnings and alerts to the behavioral steps of the monitored target.

[0011] As a further improvement of this technical solution, the behavior detection unit includes a special word capture module, a behavior element determination module and a monitoring target determination module;

[0012] The special word capturing module identifies special words on the Internet, and captures the special words after identification to obtain information about the publisher of the special words;

[0013] After the special word capturing module obtains the information of the word publisher, the behavior factor determination module determines the publisher's behavior of publishing the special word, and determines the publisher's behavior of publishing such words;

[0014] The monitoring target determination module determines the target to be monitored based on the behavior of the publisher publishing such words determined by the behavior element determination module.

[0015] As a further improvement of this technical solution, the speech monitoring unit includes a common quotation acquisition module and a behavior monitoring module;

[0016] The commonly used quotations acquisition module is used to acquire the quotations commonly used by the monitored target to obtain the speech information released by the monitored target;

[0017] The behavior monitoring module is used to monitor the information published by the monitored target, and after publishing new information, sends the newly published information of the monitored target to the commonly used quotation acquisition module, which then records it.

[0018] As a further improvement of the present technical solution, the inertia analysis unit includes a characteristic analysis module and an inertia step identification module;

[0019] The characteristic analysis module is used to analyze the characteristics of the information published by the monitored target based on the information monitored and collected by the speech monitoring unit, and obtain the behavioral characteristics of the speech frequently published by the monitored target;

[0020] The inertial step identification module is used to identify the habitual steps of the monitored target in releasing speech based on the information monitored and collected by the speech monitoring unit, and determine the speech sequence commonly released by the monitored target.

[0021] As a further improvement of this technical solution, the behavior prediction unit includes a normal speech progress analysis module and a process prediction module;

[0022] The normal speech progress analysis module is used to receive the speech sequence of the monitored target determined by the inertial step identification module, and perform normal speech progress analysis based on the determined speech sequence, determine the progress sequence of the speech posted by the monitored target on the network, and use the determined speech progress sequence as a reference;

[0023] The process prediction module is used to predict the approximate process based on the speech currently released by the monitored target, and obtain the progress position of the speech released by the monitored target in the reference process.

[0024] As a further improvement of this technical solution, the warning control unit includes a behavior step warning module and a target warning module;

[0025] The behavior step warning module is used to determine the judgment based on the process predicted by the process prediction module, and when it reaches a serious level, it will issue a system warning so that the supervisor can prepare for correction in advance;

[0026] The target warning module is used to warn the monitored target when the supervisor is preparing to make corrections, and to prevent the monitored target from making any verbal information.

[0027] As a further improvement of the present technical solution, the behavior detection unit further includes a speech information collection module, and the behavior prediction unit further includes a word collection module;

[0028] The speech information collection module is used to collect information about the person who captured the special word and the speech information published by the person when the special word capture module captures the special word;

[0029] The word collection module is used to capture the speech information released by the monitored target, and collect the information after the capture is completed.

[0030] As a further improvement of the present technical solution, the speech monitoring unit also includes a special word acquisition module, and the commonly used quotation acquisition module is used to receive the information captured by the speech information acquisition module, the special word capture module and the word collection module, and receive the commonly used quotation information of the monitored target acquired by the commonly used quotation acquisition module. At the same time, after the data in the special word acquisition module is updated, the scope of special word capture by the special word capture module is controlled.

[0031] As a further improvement of this technical solution, the speech monitoring unit further includes an activity time monitoring module;

[0032] The activity time monitoring module is used to count the time when the monitored target publishes speech, and count the time when the monitored target is active, and perform targeted monitoring on the monitored target based on the counted activity time.

[0033] As a further improvement of this technical solution, the early warning control unit also includes a network purification module;

[0034] The network purification module is used for unilaterally deleting the speech published by the monitored target when the monitored target ignores the warning after the target warning module warns the monitored target.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. In the continuous monitoring network control system with prediction function, the information of the person who made special words is determined by the set behavior detection unit, and the person is set as the monitoring target. The inertia analysis of the monitored target is performed to obtain the habit of the monitored target in making speeches, and an early warning is issued based on the speech habits. After the early warning, the monitored target is warned and the monitored target is stopped in time to prevent the monitored target from causing harm to others due to the speech. At the same time, when the warning is ineffective, the network purification module is used to perform unidirectional information deletion to prevent the spread of the speech made by the monitored target.

[0037] 2. In the continuous monitoring network control system with prediction function, the speech information of the monitored target is collected through the speech information collection module and the word collection module, and stored through the special word learning module. After storage, the stored special words are sent to the special word capture module, so that the special word capture module captures the updated special words, allowing the system to learn independently, improve the system's ability to identify newly emerging special words, and improve the special word capture module's capture effect on special words. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is an overall block diagram of the present invention;

[0039] Figure 2 is a block diagram of a behavior detection unit of the present invention;

[0040] Figure 3 This is a block diagram of the speech monitoring unit of the present invention;

[0041] Figure 4 This is a block diagram of the inertial analysis unit of the present invention;

[0042] Figure 5 It is a block diagram of the behavior prediction unit of the present invention;

[0043] Figure 6 This is a block diagram of the early warning control unit of the present invention.

[0044] The meaning of each number in the figure is:

[0045] 1. Behavior detection unit; 11. Special word capture module; 12. Speech information collection module; 13. Behavior element determination module; 14. Monitoring target determination module;

[0046] 2. Speech monitoring unit; 21. Common quotations acquisition module; 22. Behavior monitoring module; 23. Activity time monitoring module; 24. Special word acquisition module;

[0047] 3. Inertia analysis unit; 31. Characteristic analysis module; 32. Inertia step identification module;

[0048] 4. Behavioral Prediction Unit; 41. Word Collection Module; 42. Normal Quotations Progress Analysis Module; 43. Process Prediction Module;

[0049] 5. Early Warning Control Unit; 51. Behavioral Step Early Warning Module; 52. Target Warning Module; 53. Network Purification Module. Detailed Implementation Manner

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0051] Embodiment 1

[0052] The present invention provides a network control system with continuous monitoring and prediction functions, please refer to Figures 1-6 , including a behavior detection unit 1, a speech monitoring unit 2, an inertia analysis unit 3, a behavior prediction unit 4, and an early warning control unit 5;

[0053] The behavior detection unit 1 is used to search for some special words on the network and determine the monitoring target after determining the meaning of the special words; <0^000122>

[0054] The behavior detection unit 1 includes a special word capture module 11, a behavior element determination module 13, and a monitoring target determination module 14;

[0055] The special word capture module 11 identifies special words on the network and captures the special words after identification, obtaining information about the publisher of the special words, such as account information, registration address, etc., and obtaining the basic information of the publisher of the special words;

[0056] Among them, the capture of special words uses the Jaro-Winkler algorithm: The specific information of the formula is as follows:

[0057] Let the Jaro distance between two strings be d, the length of the common prefix of the two strings be L, and the range factor of the prefix be p. The calculation formula of the Jaro-Winkler distance is:

[0058] d

[0060] , = d j + L·p(1 - d j )

[0059] The character value range of L is 0 < L < 4 characters, p < 0.25, and p = 0.1;

[0060] When dw The larger the value, the greater the similarity between the two character strings. This indicates that the words published on the Internet are similar to the words to be captured by the special word capture module 11. After determining the similarity, the special word capture module 11 captures the determined special words.

[0061] After the special word capturing module 11 obtains the information of the word publisher, the behavior factor determination module 13 translates the meaning of the published word and determines the publisher's behavior of publishing the special word based on the meaning of the word, and determines what kind of behavior the publisher's behavior of publishing such a word is, such as whether it is a complaint or a joke, or an insult or ridicule to others;

[0062] The monitoring target determination module 14 determines the behavior of the publisher who publishes such words based on the behavior factor determination module 13. If the words are complaints or jokes, such words are ignored. If the words are insulting or mocking others, making personal attacks on others or damaging others' dignity, the publisher of such words is determined to be a target that needs to be monitored, and the speech monitoring unit 2 is required to monitor the publisher of such words to prevent the publisher of such words from posting other words that hurt others.

[0063] At the same time, the behavior detection unit 1 also includes a speech information collection module 12, which is used to collect information about the person who captures the special word and the speech information published by the person when the special word capture module 11 captures the special word, and temporarily store the collected information about the publisher of the special word;

[0064] The speech monitoring unit 2 is used to monitor the speech behavior of the monitoring target determined by the behavior detection unit 1, and obtain the normal behavior of the monitoring target;

[0065] The speech monitoring unit 2 includes a common quotation acquisition module 21 and a behavior monitoring module 22;

[0066] The commonly used quotations acquisition module 21 is used to acquire the quotations commonly used by the monitored target, obtain the speech information released by the monitored target later, and obtain commonly used speech information based on the speech released by the monitored target;

[0067] The behavior monitoring module 22 is used to monitor the information published by the monitored target, and after publishing new information, it sends the newly published information of the monitored target to the common quotation acquisition module 21, and the common quotation acquisition module 21 records it and extracts common speech information when recording;

[0068] When monitoring the behavior of the monitored target, it is also necessary to obtain the activity time of the monitored target so as to monitor the monitored target accordingly during the time when the monitored target is active. Therefore, the speech monitoring unit 2 further includes an activity time monitoring module 23;

[0069] The activity time monitoring module 23 is used to count the time when the monitored target publishes speech, and count the time when the monitored target is active, and perform targeted monitoring on the monitored target based on the counted activity time, thereby improving the monitoring effect on the monitored target;

[0070] At the same time, the inertia analysis unit 3 determines the inertia of the monitoring target based on the behavior normality of the speech monitoring unit 2 and obtains the inertia steps of the monitoring target;

[0071] The inertia analysis unit 3 includes a characteristic analysis module 31 and an inertia step identification module 32;

[0072] The characteristic analysis module 31 is used to analyze the characteristics of the information published by the monitored target based on the information monitored and collected by the speech monitoring unit 2, determine the effect of each speech published by the monitored target, obtain the behavioral characteristics of the speech frequently published by the monitored target, and mark the monitored target according to the behavioral characteristics, so that the marked monitored target is used as a key monitoring target;

[0073] The inertial step recognition module 32 is used to identify the habitual steps of the monitored target's speech release based on the information monitored and collected by the speech monitoring unit 2, and determine the order of speech released by the monitored target, so that the behavior prediction unit 4 can predict the release of information based on the speech order determined by the inertial step recognition module 32, so that the system can perform early control and adjustment;

[0074] The behavior prediction unit 4 is used to analyze the steps of the published speech according to the inertial steps of the monitoring target obtained by the inertia analysis unit 3, and predict the speech process of the monitoring target;

[0075] The behavior prediction unit 4 includes a normal quotation progress analysis module 42 and a process prediction module 43;

[0076] The normal speech progress analysis module 42 is used to receive the speech sequence of the monitored target determined by the inertial step identification module 32, and perform normal speech progress analysis based on the determined speech sequence, determine the progress sequence of the speech posted by the monitored target on the network, and use the determined speech progress sequence as a reference;

[0077] The process prediction module 43 is used to predict the approximate process based on the speech currently published by the monitored target, and obtain the progress position of the speech published by the monitored target in the reference process;

[0078] The behavior prediction unit 4 also includes a word collection module 41

[0079] The word collection module 41 is used to capture the speech information released by the monitored target, and after the capture is completed, the information is collected to obtain the information in the newly published speech of the monitored target. At the same time, in order to enable the system to automatically update special words, the speech monitoring unit 2 also includes a special word acquisition module 24. The commonly used quotation acquisition module 21 is used to receive the information captured by the speech information acquisition module 12, the special word capture module 11 and the word collection module 41, and receive the commonly used quotation information of the monitored target obtained by the commonly used quotation acquisition module 21. At the same time, after the data in the special word acquisition module 24 is updated, the scope of the special word capture module 11 to capture special words is controlled, so that when new words appear, the system can automatically update, so that when new nouns appear on the network, the system can acquire new nouns, so that the special word capture module 11 will not miss new words when capturing special words, so as to achieve the effect of strict control;

[0080] After determining the speech process of the monitored target, the early warning control unit 5 issues early warnings and alerts to the behavioral steps of the monitored target;

[0081] The warning control unit 5 includes a behavior step warning module 51 and a target warning module 52;

[0082] The behavior step warning module 51 is used to determine the process based on the process prediction module 43 and issue a system warning when the severity reaches a critical level, so that the supervisor can prepare for corrections in advance;

[0083] The target warning module 52 is used to warn the monitored target when the supervisor is preparing to make corrections, preventing the monitored target from making verbal information, so that the monitored target is warned and converges, thus preventing the occurrence of online violence from the root. At the same time, if the monitored target does not listen to the warning, the early warning control unit 5 also includes a network purification module 53;

[0084] The network purification module 53 is used to unilaterally delete the speech made by the monitored target when the target warning module 52 warns the monitored target and the monitored target ignores the warning, so that the speech made by the monitored target cannot be spread on the Internet, avoiding the speech made by the monitored target from affecting the lives of others. At the same time, the monitored target can see the speech he or she has made, avoiding the monitored target from getting angry because the speech has not been published, and avoiding extreme situations.

[0085] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and improvements may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and improvements fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A continuous monitoring network control system with a prediction function, characterized by: It includes a behavior detection unit (1), a speech monitoring unit (2), an inertia analysis unit (3), a behavior prediction unit (4) and an early warning control unit (5); The behavior detection unit (1) is used to search for some special words on the Internet, and after determining the meaning of the special words, determine the monitoring target; The speech monitoring unit (2) is used to monitor the speech behavior of the monitoring target determined by the behavior detection unit (1) to obtain the normal behavior of the monitoring target; The inertia analysis unit (3) performs inertia judgment of the monitoring target based on the behavior normality of the speech monitoring unit (2) to obtain the inertia steps of the monitoring target; The behavior prediction unit (4) is used to analyze the steps of the published speech according to the inertial steps of the monitoring target obtained by the inertia analysis unit (3), and predict the speech process of the monitoring target; The early warning control unit (5) issues early warnings and alerts to the behavior steps of the monitored target after determining the speech process of the monitored target; The inertia analysis unit (3) includes a characteristic analysis module (31) and an inertia step identification module (32); The characteristic analysis module (31) is used to analyze the characteristics of information published by the monitored target based on the information monitored and collected by the speech monitoring unit (2), and obtain the behavioral characteristics of the speech frequently published by the monitored target; The inertial step identification module (32) is used to identify the habitual steps of the monitored target's speech release based on the information monitored and collected by the speech monitoring unit (2), and to determine the order of speech that the monitored target often releases; The behavior prediction unit (4) includes a normal speech progress analysis module (42) and a process prediction module (43); The normal speech progress analysis module (42) is used to receive the speech sequence of the monitored target determined by the inertial step identification module (32), and perform normal speech progress analysis based on the determined speech sequence, determine the progress sequence of the speech published by the monitored target on the network, and use the determined speech progress sequence as a reference; The process prediction module (43) is used to predict the approximate process based on the speech currently released by the monitored target, and obtain the progress position of the speech released by the monitored target in the reference process.

2. The continuous monitoring network control system with prediction function according to claim 1 is characterized in that: The behavior detection unit (1) includes a special word capturing module (11), a behavior element determining module (13) and a monitoring target determining module (14); The special word capturing module (11) identifies special words on the Internet, captures the special words after identification, and obtains information about the publisher of the special words; After the special word capturing module (11) obtains the information of the word publisher, the behavior element determining module (13) determines the publisher's behavior of publishing the special word, and determines the publisher's behavior of publishing such words; The monitoring target determination module (14) determines the target to be monitored based on the behavior of the publisher who publishes such words determined by the behavior element determination module (13).

3. The continuous monitoring network control system with prediction function according to claim 1 is characterized in that: The speech monitoring unit (2) includes a common quotation acquisition module (21) and a behavior monitoring module (22); The commonly used quotation acquisition module (21) is used to acquire the commonly used quotation of the monitored target to obtain the speech information released by the monitored target; The behavior monitoring module (22) is used to monitor the information published by the monitored target, and after publishing new information, sends the newly published information of the monitored target to the commonly used quotation acquisition module (21), and the commonly used quotation acquisition module (21) records it.

4. The continuous monitoring network control system with prediction function according to claim 1 is characterized in that: The early warning control unit (5) includes a behavior step early warning module (51) and a target warning module (52); The behavior step warning module (51) is used to determine the judgment based on the process predicted by the process prediction module (43), and when the severity is reached, a system warning is issued so that the supervisor can prepare for correction in advance; The target warning module (52) is used to warn the monitored target when the supervisor is preparing to make corrections, and to prevent the monitored target from uttering verbal information.

5. The continuous monitoring network control system with prediction function according to claim 1 is characterized in that: The behavior detection unit (1) further includes a speech information acquisition module (12), and the behavior prediction unit (4) further includes a word collection module (41); The speech information collection module (12) is used to collect information about the person who has captured the special word and the speech information published by the person when the special word capture module (11) is capturing the special word; The word collection module (41) is used to capture the speech information released by the monitored target and collect the information after the capture is completed.

6. The continuous monitoring network control system with prediction function according to claim 3 is characterized in that: The speech monitoring unit (2) further includes a special word acquisition module (24), and the common quotation acquisition module (21) is used to receive information captured by the speech information acquisition module (12), the special word capture module (11), and the word collection module (41), and receive the common quotation information of the monitored target acquired by the common quotation acquisition module (21), and at the same time, after the data in the special word acquisition module (24) is updated, control the scope of special word capture by the special word capture module (11).

7. The continuous monitoring network control system with prediction function according to claim 1 is characterized in that: The speech monitoring unit (2) further includes an activity time monitoring module (23); The activity time monitoring module (23) is used to count the time when the monitored target publishes speech, and count the time when the monitored target is active, and perform targeted monitoring on the monitored target based on the counted activity time.

8. The continuous monitoring network control system with prediction function according to claim 1 is characterized in that: The early warning control unit (5) further includes a network purification module (53); The network purification module (53) is used to unilaterally delete the speech published by the monitored target when the monitored target ignores the warning after the target warning module (52) warns the monitored target.

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