CN109614449A - The method, apparatus and storage medium of mobile terminal data association analysis are carried out based on LWSVR - Google Patents
The method, apparatus and storage medium of mobile terminal data association analysis are carried out based on LWSVR Download PDFInfo
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Abstract
The embodiment of the invention discloses a kind of method, apparatus and storage medium that mobile terminal data association analysis is carried out based on LWSVR, are related to network safety filed.The method comprise the steps that obtaining mobile terminal data collection, it includes multiple mobile terminal datas that the mobile terminal data, which is concentrated,；The mobile terminal data collection is inputted into local weighted support vector regression LWSVR model, feature is extracted and obtains data characteristics collection；Each data characteristics concentrated to the data characteristics is associated analysis, obtains global data feature；Based on the global data feature, the security postures of the mobile terminal are obtained.The present invention can be improved the accuracy of mobile terminal safety Study on Trend.
Description
Technical field
The present invention relates to network safety fileds, more particularly to a kind of LWSVR that is based on to carry out mobile terminal data association analysis
Method, apparatus and storage medium.
Background technique
With the continuous development of network technology, the use of mobile terminal is also increasingly popularized, and it is not retrievable general to become user
It is equipped all over using.The analysis of the network safety situation of mobile terminal and the acquisition of potential risk hidden danger also become urgently to be resolved
Problem.Currently, mobile terminal under different application scene there are different risk hidden danger, the type of security risk is more, and situation
It is complicated, it is difficult to which that comprehensive analysis in real time is carried out to the Network Situation of mobile terminal.
Summary of the invention
The embodiment of the present invention provide it is a kind of based on LWSVR carry out mobile terminal data association analysis method, apparatus and
Storage medium can be improved the accuracy of mobile terminal safety Study on Trend.
In order to achieve the above objectives, the embodiment of the present invention adopts the following technical scheme that
In a first aspect, the embodiment of the present invention provides a kind of side for carrying out mobile terminal data association analysis based on LWSVR
Method, comprising:
Mobile terminal data collection is obtained, it includes multiple mobile terminal datas that the mobile terminal data, which is concentrated,；
The mobile terminal data collection is inputted into local weighted support vector regression LWSVR model, feature is extracted and is counted
According to feature set；
Each data characteristics concentrated to the data characteristics is associated analysis, obtains global data feature；
Based on the global data feature, the security postures of the mobile terminal are obtained.
With reference to first aspect, in the first possible implementation of the first aspect, the local weighted supporting vector
LWSVR model is returned to be made of local weighted Recurrent networks and Support Vector Regression Network, the method also includes:
Marked mobile terminal safety situation data are obtained, the marked mobile terminal safety situation data include movement
Terminal abnormal behavioral data, mobile terminal potential threat data and running of mobile terminal situation data；
By the corresponding prediction data feature of marked security postures data described in the LWSVR model extraction, and it is associated with
Analysis obtains prediction security postures；
Security postures are predicted based on the marked mobile terminal safety situation data set, and the LWSVR model is carried out
Training.
With reference to first aspect, in the second possible implementation of the first aspect, described to be based on the global data
Feature, the security postures for obtaining the mobile terminal include:
Based on the global data feature, the security postures grade of the mobile terminal, the security postures analysis are obtained
Registration includes: high-risk situation, middle danger situation, low danger situation or security postures.
With reference to first aspect, in a third possible implementation of the first aspect, the method also includes:
Based on the security postures of the mobile terminal, any one in following information or any combination are visualized:
Security postures situation, security threat data, warning information data.
With reference to first aspect, in a fourth possible implementation of the first aspect, the mobile terminal data includes
The user information of mobile terminal moves software and hardware resources, system log, using log, alarm log or error log.
Second aspect, the embodiment of the present invention provide a kind of dress that mobile terminal data association analysis is carried out based on LWSVR
It sets, comprising:
Module is obtained, for obtaining mobile terminal data collection, it includes multiple mobile terminals that the mobile terminal data, which is concentrated,
Data；
Extraction module is mentioned for the mobile terminal data collection to be inputted local weighted support vector regression LWSVR model
Feature is taken to obtain data characteristics collection；
Analysis module, each data characteristics for concentrating to the data characteristics are associated analysis, obtain global data
Feature；
Generation module obtains the security postures of the mobile terminal for being based on the global data feature.
In conjunction with second aspect, in the first possible implementation of the second aspect, described device further include:
Training module, for obtaining marked mobile terminal safety situation data, the marked mobile terminal safety state
Gesture data include mobile terminal abnormal behaviour data, mobile terminal potential threat data and running of mobile terminal situation data；It is logical
Cross the corresponding prediction data feature of marked security postures data described in the LWSVR model extraction, and association analysis obtain it is pre-
Survey security postures；Predict security postures based on the marked mobile terminal safety situation data set, to the LWSVR model into
Row training；Wherein, the local weighted support vector regression LWSVR model of the training module training is by local weighted recurrence
Network and Support Vector Regression Network are constituted.
In conjunction with second aspect, in a second possible implementation of the second aspect,
The generation module is also used to obtain the security postures etc. of the mobile terminal based on the global data feature
Grade, the security postures analysis registration includes: high-risk situation, middle danger situation, low danger situation or security postures.
In conjunction with second aspect, in the third possible implementation of the second aspect, described device further include:
Display module visualizes any one in following information for the security postures based on the mobile terminal
Kind or any combination: security postures situation, security threat data, warning information data.
In conjunction with second aspect, in the fourth possible implementation of the second aspect,
It is described to obtain the user information, mobile software and hardware money that the mobile terminal data that module obtains includes mobile terminal
Source, system log, using log, alarm log or error log.
The third aspect, the embodiment of the present invention provide a kind of computer readable storage medium, are stored thereon with computer journey
Sequence, which is characterized in that the step of method that first aspect provides is realized when described program is executed by processor.
The method, apparatus and storage provided in an embodiment of the present invention that mobile terminal data association analysis is carried out based on LWSVR
Medium, by obtaining mobile terminal data collection, it includes multiple mobile terminal datas that the mobile terminal data, which is concentrated,；By the shifting
Dynamic terminal data collection inputs local weighted support vector regression LWSVR model, extracts feature and obtains data characteristics collection；To the number
It is associated analysis according to each data characteristics in feature set, obtains global data feature；Based on the global data feature, obtain
The security postures of the mobile terminal.It can be by the LWSVR that blends local weighted network and Support Vector Regression Network
Model to carry out feature extraction to mobile terminal data, and carries out mobile terminal safety Study on Trend, can be improved mobile terminal
The accuracy and real-time of security postures analysis.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to needed in the embodiment
Attached drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for ability
For the those of ordinary skill of domain, without creative efforts, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is the process signal of the method that mobile terminal data association analysis is carried out based on LWSVR of the embodiment of the present invention
Figure；
Fig. 2 is another process of the method that mobile terminal data association analysis is carried out based on LWSVR of the embodiment of the present invention
Schematic diagram；
Fig. 3 is the apparatus structure schematic diagram that mobile terminal data association analysis is carried out based on LWSVR of the embodiment of the present invention；
Fig. 4 is another structure of the device that mobile terminal data association analysis is carried out based on LWSVR of the embodiment of the present invention
Schematic diagram；
Fig. 5 is that the structure of the device 500 for carrying out mobile terminal data association analysis based on LWSVR of the embodiment of the present invention is shown
It is intended to.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts all other
Embodiment shall fall within the protection scope of the present invention.
One embodiment of the invention provides a kind of method for carrying out mobile terminal data association analysis based on LWSVR, such as Fig. 1 institute
Show, which comprises
101, mobile terminal data collection is obtained, it includes multiple mobile terminal datas that the mobile terminal data, which is concentrated,；
102, the mobile terminal data collection is inputted into local weighted support vector regression LWSVR model, extracts feature and obtains
To data characteristics collection；
103, each data characteristics concentrated to the data characteristics is associated analysis, obtains global data feature；
104, it is based on the global data feature, obtains the security postures of the mobile terminal.
In embodiments of the present invention, it is in real time, efficiently and accurately perceives mobile terminal safety situation, using based on machine
The local weighted support vector regression LWSVR algorithm of study to the user information of mobile terminal, mobile terminal self-information, is
The secure datas such as system log, running log, alarm and error log are associated to be analyzed with merger, and there are internal associations for integration
Security information is capable of forming self study security postures feature database.
Local weighted support vector regression (LWSVR) is the side for blending local weighted recurrence and support vector regression
Method can effectively play respective advantage, improve the accuracy of terminal security data Study on Trend, can promptly and accurately divide
The security postures situation of mobile terminal is precipitated, and is reflected to mobile terminal user or management in the form of visualization interface
Person.
Compared with prior art, the embodiment of the present invention can be by by local weighted network and Support Vector Regression Network phase
The LWSVR model of fusion to carry out feature extraction to mobile terminal data, and carries out mobile terminal safety Study on Trend, Neng Gouti
The accuracy and real-time of high mobile terminal safety Study on Trend.
Further embodiment of this invention provides a kind of method for carrying out mobile terminal data association analysis based on LWSVR, such as Fig. 2
It is shown, which comprises
201, mobile terminal data collection is obtained, it includes multiple mobile terminal datas that the mobile terminal data, which is concentrated,.
The mobile terminal data includes the user information of mobile terminal, movement software and hardware resources, system log, using day
Will, alarm log or error log.
202, the mobile terminal data collection is inputted into local weighted support vector regression LWSVR model, extracts feature and obtains
To data characteristics collection.
Wherein, the local weighted support vector regression LWSVR model is returned by local weighted Recurrent networks and supporting vector
Network is returned to constitute.In embodiments of the present invention, local weighted support vector regression (LWSVR) algorithm be by it is local weighted recurrence and
The method that support vector regression blends can effectively play respective advantage, improve terminal security data Study on Trend
Accuracy, can promptly and accurately analyze the security postures situation of mobile terminal, and is reflected in the form of visualization interface
Mobile terminal user or manager.
For the embodiment of the present invention, LWSVR model can be trained by the following method: being obtained marked mobile whole
Security postures data are held, the marked mobile terminal safety situation data include mobile terminal abnormal behaviour data, move eventually
Hold potential threat data and running of mobile terminal situation data；Pass through marked security postures described in the LWSVR model extraction
The corresponding prediction data feature of data, and association analysis obtains prediction security postures；Based on the marked mobile terminal safety
Situation data set predicts security postures, is trained to the LWSVR model.
203, each data characteristics concentrated to the data characteristics is associated analysis, obtains global data feature.
204, it is based on the global data feature, obtains the security postures grade of the mobile terminal, the security postures
Analysis registration includes: high-risk situation, middle danger situation, low danger situation or security postures.
In embodiments of the present invention, high-risk rank represents mobile terminal safety situation and is in high state of necessity, it is proposed that vertical
Corresponding measure is taken to repair security risk existing for it；Middle danger rank represents mobile terminal safety situation and is in medium
State of necessity, it is proposed that corresponding measure is taken to repair its security risk；Low danger rank represents at mobile terminal safety situation
In low precarious position；Safety representatives mobile terminal is currently in safe condition.
205, the security postures based on the mobile terminal visualize any one in following information or any group
It closes: security postures situation, security threat data, warning information data.
Wherein, the warning information data for pushing and visualizing include but is not limited to: phone number, IP address, affiliated
Unit, notification the time, notification title, circulation scope, notification source, notification state (wait notify, notified, it is to be processed, processing
In, be completed) etc..
For the embodiment of the present invention, the content of the visual presentation further includes following any one or any combination: pre-
If the mobile terminal safety total number of events captured in the period, security incident quantity category statistics, security incident quantity are by threat
Degree statistics, safe early warning notification sum, safe early warning notification category statistics, mobile terminal liveness ranking, mobile terminal
By the service condition statistics in region, app installation situation ranking, terminal security situation statistics, high-risk terminal ranking.
In embodiments of the present invention, abstract secure data can be changed by visualizing as the appreciable letter of people
Breath, magnanimity isomeric data is showed in a manner of graph image, make Security Officer it is observed that in secure data imply
Mode can quickly find rule and find potential threaten；By data processing, data fusion, Study on Trend, synthesis is formed
, global network security postures figure, carry out multiple view, multi-angle, multiple dimensioned visualization display.
Local weighted support vector regression (LWSVR) is the side for blending local weighted recurrence and support vector regression
Method can effectively play respective advantage, improve the accuracy of terminal security data Study on Trend, can promptly and accurately divide
The security postures situation of mobile terminal is precipitated, and is reflected to mobile terminal user or management in the form of visualization interface
Person.
Compared with prior art, the embodiment of the present invention can be by by local weighted network and Support Vector Regression Network phase
The LWSVR model of fusion to carry out feature extraction to mobile terminal data, and carries out mobile terminal safety Study on Trend, Neng Gouti
The accuracy and real-time of high mobile terminal safety Study on Trend.
Further embodiment of this invention provides a kind of device that mobile terminal data association analysis is carried out based on LWSVR, such as Fig. 3
Shown, described device includes:
Module 31 is obtained, for obtaining mobile terminal data collection, the mobile terminal data is concentrated comprising multiple mobile whole
End data；
Extraction module 32, for the mobile terminal data collection to be inputted local weighted support vector regression LWSVR model,
It extracts feature and obtains data characteristics collection；
Analysis module 33, each data characteristics for concentrating to the data characteristics are associated analysis, obtain global number
According to feature；
Generation module 34 obtains the security postures of the mobile terminal for being based on the global data feature.
Further, as shown in figure 4, described device further include:
Training module 41, for obtaining marked mobile terminal safety situation data, the marked mobile terminal safety
Situation data include mobile terminal abnormal behaviour data, mobile terminal potential threat data and running of mobile terminal situation data；
By the corresponding prediction data feature of marked security postures data described in the LWSVR model extraction, and association analysis obtains
Predict security postures；Security postures are predicted based on the marked mobile terminal safety situation data set, to the LWSVR model
It is trained；Wherein, the local weighted support vector regression LWSVR model of the training module training is by local weighted time
Network and Support Vector Regression Network is returned to constitute.
The generation module 34 is also used to obtain the security postures of the mobile terminal based on the global data feature
Grade, the security postures analysis registration includes: high-risk situation, middle danger situation, low danger situation or security postures.
Display module 42 visualizes any in following information for the security postures based on the mobile terminal
A kind of or any combination: security postures situation, security threat data, warning information data.
It is described to obtain the user information, mobile software and hardware that the mobile terminal data that module 31 obtains includes mobile terminal
Resource, system log, using log, alarm log or error log.
Compared with prior art, the embodiment of the present invention can be by by local weighted network and Support Vector Regression Network phase
The LWSVR model of fusion to carry out feature extraction to mobile terminal data, and carries out mobile terminal safety Study on Trend, Neng Gouti
The accuracy and real-time of high mobile terminal safety Study on Trend.
The embodiment of the present invention also provides another computer readable storage medium, which can be
Computer readable storage medium included in memory in above-described embodiment；It is also possible to individualism, eventually without supplying
Computer readable storage medium in end.The computer-readable recording medium storage has one or more than one program, institute
State that one or more than one program by one or more than one processor are used to execute Fig. 1, embodiment illustrated in fig. 2 provides
Based on LWSVR carry out mobile terminal data association analysis method.
The device provided in an embodiment of the present invention for carrying out mobile terminal data association analysis based on LWSVR may be implemented above-mentioned
The embodiment of the method for offer, concrete function realize the explanation referred in embodiment of the method, and details are not described herein.The present invention is implemented
What example provided, which carries out the method, apparatus of mobile terminal data association analysis and storage medium based on LWSVR, can be adapted for shifting
Dynamic terminal carries out security postures analysis, but is not limited only to this.
As shown in figure 5, can be mobile phone based on the LWSVR device 500 for carrying out mobile terminal data association analysis, count
Calculation machine, digital broadcasting terminal, messaging device, game console, tablet device, personal digital assistant etc..
Referring to Fig. 5, based on the LWSVR device 500 for carrying out mobile terminal data association analysis may include with next or
Multiple components: processing component 502, memory 504, power supply module 506, multimedia component 508, audio component 510, input/defeated
The interface 512 of (I/O) out, sensor module 514 and communication component 516.
Processing component 502 usually control unmanned aerial vehicle (UAV) control device 500 integrated operation, such as with display, call, number
According to communication, camera operation and record operate associated operation.Processing component 502 may include one or more processors 520
To execute instruction.
In addition, processing component 502 may include one or more modules, convenient between processing component 502 and other assemblies
Interaction.For example, processing component 502 may include multi-media module, with facilitate multimedia component 508 and processing component 502 it
Between interaction.
Memory 504 is configured as storing various types of data to support the operation in unmanned aerial vehicle (UAV) control device 500.This
The example of a little data includes the instruction of any application or method for operating on unmanned aerial vehicle (UAV) control device 500, connection
Personal data, telephone book data, message, picture, video etc..Memory 504 can be by any kind of volatibility or non-volatile
It stores equipment or their combination is realized, such as static random access memory (SRAM), the read-only storage of electrically erasable
Device (EEPROM), Erasable Programmable Read Only Memory EPROM (EPROM), programmable read only memory (PROM), read-only memory
(ROM), magnetic memory, flash memory, disk or CD.
Power supply module 506 provides electric power for the various assemblies of unmanned aerial vehicle (UAV) control device 500.Power supply module 506 may include
Power-supply management system, one or more power supplys and other with for unmanned aerial vehicle (UAV) control device 500 generate, manage, and distribute electric power phase
Associated component.
Multimedia component 508 includes one output interface of offer between the unmanned aerial vehicle (UAV) control device 500 and user
Screen.In some embodiments, screen may include liquid crystal display (LCD) and touch panel (TP).If screen includes
Touch panel, screen may be implemented as touch screen, to receive input signal from the user.Touch panel includes one or more
A touch sensor is to sense the gesture on touch, slide, and touch panel.The touch sensor can not only sense touch
Or the boundary of sliding action, but also detect duration and pressure associated with the touch or slide operation.In some realities
It applies in example, multimedia component 508 includes a front camera and/or rear camera.When unmanned aerial vehicle (UAV) control device 500 is in
Operation mode, such as in a shooting mode or a video mode, front camera and/or rear camera can receive external multimedia
Data.Each front camera and rear camera can be a fixed optical lens system or there is focal length and optics to become
Burnt ability.
Audio component 510 is configured as output and/or input audio signal.For example, audio component 510 includes a Mike
Wind (MIC), when unmanned aerial vehicle (UAV) control device 500 is in operation mode, when such as call mode, recording mode, and voice recognition mode,
Microphone is configured as receiving external audio signal.The received audio signal can be further stored in memory 504 or
It is sent via communication component 516.In some embodiments, audio component 510 further includes a loudspeaker, for exporting audio letter
Number.
I/O interface 512 provides interface between processing component 502 and peripheral interface module, and above-mentioned peripheral interface module can
To be keyboard, click wheel, button etc..These buttons may include, but are not limited to: home button, volume button, start button and lock
Determine button.
Sensor module 514 includes one or more sensors, for providing various aspects for unmanned aerial vehicle (UAV) control device 500
Status assessment.For example, sensor module 514 can detecte the state that opens/closes of unmanned aerial vehicle (UAV) control device 500, component
Relative positioning, such as the component is the display and keypad of unmanned aerial vehicle (UAV) control device 500, and sensor module 514 may be used also
To detect the position change of 500 1 components of unmanned aerial vehicle (UAV) control device 500 or unmanned aerial vehicle (UAV) control device, user and unmanned aerial vehicle (UAV) control
The existence or non-existence that device 500 contacts, 500 orientation of unmanned aerial vehicle (UAV) control device or acceleration/deceleration and unmanned aerial vehicle (UAV) control device 500
Temperature change.Sensor module 514 may include proximity sensor, be configured to examine without any physical contact
Survey presence of nearby objects.Sensor module 514 can also include that optical sensor is used for such as CMOS or ccd image sensor
It is used in imaging applications.In some embodiments, which can also include acceleration transducer, and gyroscope passes
Sensor, Magnetic Sensor, pressure sensor or temperature sensor.
Communication component 516 is configured to facilitate wired or wireless way between unmanned aerial vehicle (UAV) control device 500 and other equipment
Communication.Unmanned aerial vehicle (UAV) control device 500 can access the wireless network based on communication standard, such as WiFi, 2G or 3G or they
Combination.In one exemplary embodiment, communication component 516 is received via broadcast channel from the wide of external broadcasting management system
Broadcast signal or broadcast related information.In one exemplary embodiment, the communication component 516 further includes near-field communication (NFC)
Module, to promote short range communication.For example, radio frequency identification (RFID) technology, Infrared Data Association (IrDA) can be based in NFC module
Technology, ultra wide band (UWB) technology, bluetooth (BT) technology and other technologies are realized.
In the exemplary embodiment, unmanned aerial vehicle (UAV) control device 500 can be by one or more application specific integrated circuit
(ASIC), digital signal processor (DSP), digital signal processing appts (DSPD), programmable logic device (PLD), scene can
Gate array (FPGA), controller, microcontroller, microprocessor or other electronic components are programmed to realize.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for equipment reality
For applying example, since it is substantially similar to the method embodiment, so describing fairly simple, related place is referring to embodiment of the method
Part explanation.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the program can be stored in a computer-readable storage medium
In, the program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, the storage medium can be magnetic
Dish, CD, read-only memory (Read-Only Memory, ROM) or random access memory (RandomAccess
Memory, RAM) etc..
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
In the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of by those familiar with the art, all answers
It is included within the scope of the present invention.Therefore, protection scope of the present invention should be subject to the protection scope in claims.
Claims (11)
1. a kind of method for carrying out mobile terminal data association analysis based on LWSVR characterized by comprising
Mobile terminal data collection is obtained, it includes multiple mobile terminal datas that the mobile terminal data, which is concentrated,；
The mobile terminal data collection is inputted into local weighted support vector regression LWSVR model, feature is extracted and obtains data spy
Collection；
Each data characteristics concentrated to the data characteristics is associated analysis, obtains global data feature；
Based on the global data feature, the security postures of the mobile terminal are obtained.
2. the method according to claim 1 for carrying out mobile terminal data association analysis based on LWSVR, which is characterized in that
The local weighted support vector regression LWSVR model is made of local weighted Recurrent networks and Support Vector Regression Network, institute
State method further include:
Marked mobile terminal safety situation data are obtained, the marked mobile terminal safety situation data include mobile terminal
Abnormal behaviour data, mobile terminal potential threat data and running of mobile terminal situation data；
By the corresponding prediction data feature of marked security postures data described in the LWSVR model extraction, and association analysis
Obtain prediction security postures；
Security postures are predicted based on the marked mobile terminal safety situation data set, and the LWSVR model is trained.
3. the method according to claim 1 for carrying out mobile terminal data association analysis based on LWSVR, which is characterized in that
Described to be based on the global data feature, the security postures for obtaining the mobile terminal include:
Based on the global data feature, the security postures grade of the mobile terminal, the security postures analysis registration are obtained
It include: high-risk situation, middle danger situation, low danger situation or security postures.
4. the method according to claim 1 for carrying out mobile terminal data association analysis based on LWSVR, which is characterized in that
The method also includes:
Based on the security postures of the mobile terminal, any one in following information or any combination are visualized: safety
Situation situation, security threat data, warning information data.
5. the method according to claim 1 for carrying out mobile terminal data association analysis based on LWSVR, which is characterized in that
The mobile terminal data includes the user information of mobile terminal, moves software and hardware resources, system log, using log, alarm
Log or error log.
6. a kind of device for carrying out mobile terminal data association analysis based on LWSVR characterized by comprising
Module is obtained, for obtaining mobile terminal data collection, it includes multiple mobile terminal datas that the mobile terminal data, which is concentrated,；
Extraction module extracts special for the mobile terminal data collection to be inputted local weighted support vector regression LWSVR model
Obtain data characteristics collection；
Analysis module, each data characteristics for concentrating to the data characteristics are associated analysis, obtain global data feature；
Generation module obtains the security postures of the mobile terminal for being based on the global data feature.
7. the device according to claim 6 for carrying out mobile terminal data association analysis based on LWSVR, which is characterized in that
Described device further include:
Training module, for obtaining marked mobile terminal safety situation data, the marked mobile terminal safety situation number
According to including mobile terminal abnormal behaviour data, mobile terminal potential threat data and running of mobile terminal situation data；Pass through institute
The corresponding prediction data feature of marked security postures data described in LWSVR model extraction is stated, and association analysis obtains prediction peace
Full situation；Security postures are predicted based on the marked mobile terminal safety situation data set, and the LWSVR model is instructed
Practice；Wherein, the local weighted support vector regression LWSVR model of the training module training is by local weighted Recurrent networks
It is constituted with Support Vector Regression Network.
8. the device according to claim 6 for carrying out mobile terminal data association analysis based on LWSVR, which is characterized in that
The generation module is also used to obtain the security postures grade of the mobile terminal, institute based on the global data feature
Stating security postures analysis registration includes: high-risk situation, middle danger situation, low danger situation or security postures.
9. the device according to claim 6 for carrying out mobile terminal data association analysis based on LWSVR, which is characterized in that
Described device further include:
Display module, for the security postures based on the mobile terminal, visualize in following information any one or
Any combination: security postures situation, security threat data, warning information data.
10. the device according to claim 6 for carrying out mobile terminal data association analysis based on LWSVR, which is characterized in that
It is described obtain user information, mobile software and hardware resources that the mobile terminal data that module obtains includes mobile terminal,
System log, using log, alarm log or error log.
11. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that described program is processed
The step of claim 1-5 the method is realized when device executes.
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