CN114466316A - Big data user behavior encryption management system and method - Google Patents
Big data user behavior encryption management system and method Download PDFInfo
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- CN114466316A CN114466316A CN202210381114.XA CN202210381114A CN114466316A CN 114466316 A CN114466316 A CN 114466316A CN 202210381114 A CN202210381114 A CN 202210381114A CN 114466316 A CN114466316 A CN 114466316A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/02—Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
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Abstract
The invention relates to the technical field of information encryption, and discloses a user behavior encryption management system and a user behavior encryption management method for big data, wherein the user behavior encryption management system for the big data comprises the following steps: and the information acquisition module is used for acquiring the user information of the mobile terminal and acquiring the user behavior in real time. And the positioning module is used for acquiring the current position of the mobile terminal. And the time acquisition module is used for acquiring the time point. And the random messy code module is used for extracting the random code of the coding method. And the coding module is used for coding the obtained information structure to form monitoring information. And the signal receiving module receives the transmission signal and converts the transmission signal into monitoring information. And the reverse messy code module performs reverse operation on the information structure according to the random code. The time acquisition module extracts time points. The time sequencing module sequences the personnel information, the current position and the user behavior. And the information combination module is used for combining the information. The invention carries out random coding during signal transmission and has good security effect.
Description
Technical Field
The invention relates to the technical field of information encryption, in particular to a user behavior encryption management system and method for big data.
Background
With the development of science and technology, people enter the information era, the functions of the mobile terminal are improved day by day, the role of the mobile terminal in the daily life and work of people is important day by day, and meanwhile, the safety of the mobile terminal and the privacy of users are concerned more and more. At present, most mobile terminals support encryption functions, including supporting encryption functions for mobile terminal screens, such as the current password screen locking function; supporting encryption functions for files in the mobile terminal, such as current album and photo album encryption functions; and so on.
However, the existing encryption password cannot be used universally on the mobile terminal, and cannot meet different encryption requirements of different levels of strength and different application scenes. In addition, the existing password encryption is easy to be peeped by others, and the security degree is not high.
Disclosure of Invention
In order to solve the above technical problem, the present invention provides a big data user behavior encryption management system, including:
the information acquisition module is used for acquiring the user information of the mobile terminal, searching a preset information-monitoring personnel information table through the user information, judging whether the information belongs to monitoring personnel, and if not, not performing information acquisition; if yes, judging that the monitoring personnel are monitored, acquiring information of the monitoring personnel and acquiring user behaviors in real time;
the positioning module is used for positioning the mobile terminal and acquiring the current position of the mobile terminal;
the time acquisition module is used for acquiring the time point of current user information acquisition;
the random messy code module is used for randomly extracting a coding method from a preset coding method library and extracting a random code of the coding method;
the coding module is used for receiving personnel information, the current position, the time point and the user behavior, coding according to the coding method to obtain an information structure, implanting a random code and combining the random code into monitoring information;
the signal receiving module is used for receiving the transmission signal and converting the transmission signal into monitoring information;
the random code acquisition module is used for receiving the monitoring information, extracting a random code from the monitoring information and acquiring an information structure;
the reverse messy code module is used for receiving the monitoring information and performing reverse operation on the information structure according to the random code;
the time acquisition module is used for receiving the personnel information, the current position, the time point and the user behavior and extracting the time point;
the time sequencing module is used for sequencing the personnel information, the current position and the user behavior through a time point;
and the information combination module is used for receiving the personnel information, the current position and the user behavior which are sequenced according to time and combining the personnel information, the current position and the user behavior.
Preferably: the information acquisition module comprises one or more of a voice receiver, a touch screen and a camera.
Preferably: the user information includes one or more of sound information, fingerprint information, and face information.
Preferably: when the information acquisition module is a voice receiver, the information acquisition module comprises a noise recognition module, a noise removal module and a voice data amplification module, the noise recognition module is used for analyzing the voice information and decomposing the voice information into voice data and noise, the noise removal module is used for filtering the noise in the voice information to obtain pure voice data, and the voice data amplification module is used for amplifying the voice data to preset decibel intensity.
Preferably: the information acquisition module further comprises a voice correction module, and the voice correction module is used for converting non-standard voice information into standard voice information.
Preferably: the user behavior encryption management system for the big data further comprises a behavior type identification module, wherein the behavior type identification module is used for receiving the current position and the time point of the mobile terminal, searching according to a preset personnel-position-time comparison table and obtaining the current monitoring level.
Preferably: judging whether the current monitoring level is greater than a preset authority level, and if not, sending a prompt signal; when the prompting signal appears twice in a specified interval time, the warning signal is sent. And when the prompt signal appears three times, sending an alarm signal and sending a current location position and personnel information signal.
The invention also provides a user behavior encryption management method of big data, which is used for the user behavior encryption management system of the big data, and the user behavior encryption management method of the big data comprises the following steps:
s1, acquiring user information of the mobile terminal;
s2, searching a preset information-monitoring personnel information table through the user information, judging whether the user belongs to monitoring personnel, and if so, executing S3;
s3, judging the monitoring personnel, acquiring information of the monitoring personnel and acquiring user behaviors in real time;
s4, acquiring the current position and the time point of the mobile terminal;
s5, randomly extracting a coding method from a preset coding method library, and extracting a random code of the coding method;
s6, encoding the personnel information, the current position, the time point and the user behavior according to the encoding method to obtain an information structure, implanting a random code, and combining the random code into monitoring information;
s7, transmitting the monitoring information;
s8, extracting a random code from the monitoring information and obtaining an information structure;
s9, performing reverse operation on the information structure according to the random code;
s10, extracting time points;
s11, sequencing the personnel information, the current position and the user behavior through the time point;
s12, personnel information sorted by time, current location, user behavior, and combining.
The invention also provides a computer terminal, which is used for realizing the steps of the big data user behavior encryption management method when executing the computer program stored in the memory.
The present invention also provides a computer-readable storage medium having a computer program stored thereon; and when the program is executed by the processor, the steps of the user behavior encryption management method of the big data are realized.
The invention has the technical effects and advantages that: the invention carries out random coding during signal transmission, and has very good confidentiality because the information transmission methods are different every time. The user information is acquired through various ways, and the information content is rich. The monitoring information is discharged through time, so that different types of information can be organically combined, and observation and collection are facilitated.
Drawings
Fig. 1 is a block diagram of a big data user behavior encryption management system according to the present invention.
Fig. 2 is a flowchart of a user behavior encryption management method for big data according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. The embodiments of the present invention have been presented for purposes of illustration and description, and are not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiment was chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.
Example 1
Referring to fig. 1, in the present embodiment, a system for managing user behavior encryption of big data is provided, including:
the information acquisition module is used for acquiring the user information of the mobile terminal, searching a preset information-monitoring personnel information table through the user information, judging whether the user belongs to monitoring personnel, and if not, not performing information acquisition; if yes, judging the monitoring personnel, acquiring information of the monitoring personnel and acquiring user behaviors in real time. The information acquisition module may be one or more of a voice receiver, a touch screen, and a camera, and the user information corresponding to the information acquisition module may include one or more of voice information, fingerprint information, and facial information. The user behavior may be voice information, touch screen display information and finger contact content, video information, and the like. For example, the information acquisition module is a voice receiver, receives the voice information, judges the voice information according to the tone, the audio frequency and the like of the voice information, and searches a preset information-monitoring personnel information table (tone, audio frequency-monitoring personnel information table) for the tone and the audio frequency of the voice information to compare, and the personnel identity can be identified due to the fact that the tone and the audio frequency of different people are different. And judging the monitoring personnel and acquiring the voice information of the monitoring personnel in real time. Of course, the fingerprint information and face information comparison methods are basically the same, and are not described herein in detail.
When the information acquisition module is speech receiver, the information acquisition module can include noise identification module, noise removal module and speech data amplifier module, noise identification module is used for carrying out the analysis to speech information to decompose speech information into speech data and noise, the noise removal module is arranged in filtering the noise in the speech information and obtains simple speech data, speech data amplifier module is used for enlargiing speech data to a preset decibel intensity, thereby be convenient for handle. The information acquisition module further comprises a voice correction module, and the voice correction module is used for converting non-standard voice information into standard voice information, so that processing is facilitated, and the conversion accuracy is improved. In many places there are different dialects, which have inaccurate pronunciation and, if speech correction is not performed, inaccurate translation. The same pronunciation deviation exists in the same place, and the correction scheme is set according to the regional characteristics, so that the correction is accurate.
A positioning module for positioning the mobile terminal and obtaining the current position s of the mobile terminaliThe current position may be an array of positions, respectively s1、s2、…si、…sn. The mobile terminal can move and update in real time.
A time acquisition module for acquiring the time point t of the current user information acquisitioniThe time point may be a time array, t1、t2…ti…tn。
A behavior type identification module for receiving the current position s of the mobile terminaliAnd a point in time tiAnd searching according to a preset personnel-position-time comparison table to obtain the current monitoring grade. Current monitoring levelThe initial level may be increased or decreased according to the initial level information of the monitoring personnel and according to the difference of the position and time of the initial level, which is not described herein in detail. Judging whether the current monitoring level is greater than a preset authority level, and if not, sending a prompt signal; when the prompting signal appears twice in a specified interval time, the warning signal is sent. And when the prompt signal appears three times, sending an alarm signal and sending a current location position and personnel information signal.
And the random messy code module randomly extracts a coding method from a preset coding method library and extracts a random code of the coding method. The encoding method may be reverse order, interval arrangement, etc., and is not described herein in detail.
And the coding module is used for receiving personnel information, the current position, the time point and the user behavior, coding according to the coding method to obtain an information structure, implanting a random code and combining the random code into monitoring information. For example, the encoding method at this time is a reverse order, the person information, the current position, the time point, and the user behavior are arranged in the reverse order as the user behavior, the time point, the current position, and the person information, and the random code of the reverse order is N, so the monitoring information may be N-user behavior, time point, current position, and person information. And the signal sending module is used for receiving the monitoring information and converting the monitoring information into a transmission signal.
And the signal receiving module is used for receiving the transmission signal and converting the transmission signal into monitoring information.
And the random code acquisition module is used for receiving the monitoring information, extracting a random code from the monitoring information and acquiring an information structure.
And the reverse messy code module is used for receiving the monitoring information and performing reverse operation on the information structure according to the random code. For example, the coding method is reverse order by N. And carrying out reverse order arrangement on the user behaviors, the time points, the current positions and the personnel information to obtain the personnel information, the current positions, the time points and the user behaviors. The security is very good because the method of each information transmission is different.
A time acquisition module for receiving the personal informationInformation, current position, time point and user behavior, and extracting time point ti。
A time sequencing module for passing the time point tiAnd sequencing the personnel information, the current position and the user behavior. Personnel information, the current position and user behaviors, wherein the user behaviors may comprise sound information, fingerprint information and facial information, and the information is sequenced through a time point, so that the mobile terminal can be better monitored, and information can be better acquired.
And the information combination module receives the personnel information, the current position and the user behavior which are sequenced according to time, combines the personnel information, the current position and the user behavior and outputs the monitoring information. The combination is not simply pieced together, for example, the current position is displayed on a map, and user behaviors are organically combined, which is not described herein in detail.
Example 2
Referring to fig. 2, the present invention further provides a user behavior encryption management method for big data, which is used in the user behavior encryption management system for big data, where the user behavior encryption management method for big data includes:
and S1, acquiring the user information of the mobile terminal.
S2, searching a preset information-monitoring personnel information table through the user information, judging whether the user belongs to the monitoring personnel, and if so, executing S3.
And S3, judging the monitoring personnel, acquiring information of the monitoring personnel and acquiring user behaviors in real time.
And S4, acquiring the current position and the time point of the mobile terminal.
S5, randomly extracting a coding method from a preset coding method library, and extracting the random code of the coding method.
And S6, coding the personnel information, the current position, the time point and the user behavior according to the coding method to obtain an information structure, implanting a random code, and combining the random code into monitoring information.
And S7, transmitting the monitoring information.
And S8, extracting the random code from the monitoring information and obtaining an information structure.
And S9, performing inverse operation on the information structure according to the random code.
And S10, extracting time points.
And S11, sequencing the personnel information, the current position and the user behavior through the time points.
S12, personnel information sorted by time, current location, user behavior, and combining.
Example 3
A computer terminal is provided as a preferred embodiment of the present invention, and the computer terminal is configured to implement the steps of the above-mentioned user behavior encryption management method for big data when executing a computer program stored in a memory. The computer terminal can be a computer, a smart phone, a control system, other internet of things equipment and the like. The user behavior encryption management method for big data can also be designed into an embedded running program and installed on a computer terminal, such as a single chip microcomputer.
A computer-readable storage medium is provided as a preferred embodiment of the present invention, which stores a computer program having the computer program stored thereon. And when the program is executed by the processor, the steps of the user behavior encryption management method of the big data are realized. When the user behavior encryption management method for big data is applied, the user behavior encryption management method can be applied in the form of software, such as a program which is designed to be independently operated by a computer readable storage medium, wherein the computer readable storage medium can be a U disk and is designed to be a U shield, and the U disk is designed to be a program which starts the whole method through external triggering.
When being executed by a processor, the computer program realizes the steps of the user behavior encryption management method for the big data.
It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by one of ordinary skill in the art and related arts based on the embodiments of the present invention without any creative effort, shall fall within the protection scope of the present invention. Structures, devices, and methods of operation not specifically described or illustrated herein are generally practiced in the art without specific recitation or limitation.
Claims (10)
1. The big data user behavior encryption management system is characterized by comprising the following components:
the information acquisition module is used for acquiring the user information of the mobile terminal, searching a preset information-monitoring personnel information table through the user information, judging whether the information belongs to monitoring personnel, and if not, not performing information acquisition; if yes, judging that the monitoring personnel are monitored, acquiring information of the monitoring personnel and acquiring user behaviors in real time;
the positioning module is used for positioning the mobile terminal and acquiring the current position of the mobile terminal;
the time acquisition module is used for acquiring the time point of current user information acquisition;
the random messy code module is used for randomly extracting a coding method from a preset coding method library and extracting a random code of the coding method;
the coding module is used for receiving personnel information, the current position, the time point and the user behavior, coding according to the coding method to obtain an information structure, implanting a random code and combining the random code into monitoring information;
the signal receiving module is used for receiving the transmission signal and converting the transmission signal into monitoring information;
the random code acquisition module is used for receiving the monitoring information, extracting a random code from the monitoring information and acquiring an information structure;
the reverse messy code module is used for receiving the monitoring information and performing reverse operation on the information structure according to the random code;
the time acquisition module is used for receiving the personnel information, the current position, the time point and the user behavior and extracting the time point;
the time sequencing module is used for sequencing the personnel information, the current position and the user behavior through a time point;
and the information combination module is used for receiving the personnel information, the current position and the user behavior which are sequenced according to time and combining the personnel information, the current position and the user behavior.
2. The big data user behavior encryption management system according to claim 1, wherein the information acquisition module comprises one or more of a voice receiver, a touch screen, and a camera.
3. The big data user behavior encryption management system according to claim 2, wherein the user information comprises one or more of sound information, fingerprint information, and face information.
4. The system according to claim 1, wherein when the information acquisition module is a voice receiver, the information acquisition module comprises a noise recognition module, a noise removal module and a voice data amplification module, the noise recognition module is configured to analyze the voice information and decompose the voice information into voice data and noise, the noise removal module is configured to filter out noise in the voice information to obtain pure voice data, and the voice data amplification module is configured to amplify the voice data to a preset decibel intensity.
5. The big data user behavior encryption management system according to claim 4, wherein the information obtaining module further comprises a voice correction module, and the voice correction module is configured to convert non-standard voice information into standard voice information.
6. The system for encrypted management of user behavior of big data according to claim 1, further comprising a behavior type recognition module, configured to receive a current location and a time point of the mobile terminal, and perform lookup according to a preset personnel-location-time comparison table to obtain a current monitoring level.
7. The big data user behavior encryption management system according to claim 6, wherein judging whether the current monitoring level is greater than a preset authority level, if not, sending a prompt signal; sending a warning signal when the prompt signal appears twice at a specified interval time; and when the prompt signal appears for three times, sending an alarm signal, and sending a current location position and personnel information signal.
8. A big data user behavior encryption management method, which is used in the big data user behavior encryption management system according to any one of claims 1 to 7, and the big data user behavior encryption management method comprises:
s1, acquiring user information of the mobile terminal;
s2, searching a preset information-monitoring personnel information table through the user information, judging whether the user belongs to the monitoring personnel, and if so, executing S3;
s3, judging the monitoring personnel, acquiring information of the monitoring personnel and acquiring user behaviors in real time;
s4, acquiring the current position and the time point of the mobile terminal;
s5, randomly extracting a coding method from a preset coding method library, and extracting a random code of the coding method;
s6, encoding the personnel information, the current position, the time point and the user behavior according to the encoding method to obtain an information structure, implanting a random code, and combining the random code into monitoring information;
s7, transmitting the monitoring information;
s8, extracting a random code from the monitoring information and obtaining an information structure;
s9, performing inverse operation on the information structure according to the random code;
s10, extracting time points;
s11, sequencing the personnel information, the current position and the user behavior through the time point;
s12, personnel information sorted by time, current location, user behavior, and combining.
9. A computer terminal, characterized in that the computer terminal is used for implementing the steps of the big data user behavior encryption management method according to claim 8 when executing the computer program stored in the memory.
10. A computer-readable storage medium storing a computer program, the computer program being stored on a computer-readable storage medium, wherein when the program is executed by a processor, the steps of the method for user behavior encryption management of big data according to claim 8 are implemented.
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Application publication date: 20220510 |