CN112087744B - Method, system, device and storage medium for identifying terminal model - Google Patents

Method, system, device and storage medium for identifying terminal model Download PDF

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Publication number
CN112087744B
CN112087744B CN202010849133.1A CN202010849133A CN112087744B CN 112087744 B CN112087744 B CN 112087744B CN 202010849133 A CN202010849133 A CN 202010849133A CN 112087744 B CN112087744 B CN 112087744B
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terminal
acquiring
model
network access
ticket
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CN112087744A (en
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林宇扬
梁勇华
杨万山
关泽明
陈卫康
梁振宇
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Eastone Century Technology Co ltd
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Eastone Century Technology Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W8/00—Network data management
    • H04W8/22—Processing or transfer of terminal data, e.g. status or physical capabilities
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/20—Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W8/00—Network data management
    • H04W8/18—Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Databases & Information Systems (AREA)
  • Information Transfer Between Computers (AREA)

Abstract

The invention discloses a method, a system, a device and a storage medium for identifying a terminal model, wherein the method comprises the following steps: acquiring a type allocation code of a terminal; acquiring model information of the terminal according to the type distribution code and a terminal identification library, and identifying the model of the terminal; the terminal identification library is constructed and obtained based on network signaling data. The invention adopts network signaling data to construct the terminal identification feature library, so that the identification type distribution code corresponds to the terminal model, most terminals accessing to the Internet of things can be identified, the coverage rate of the terminal identification is high, and the invention can be widely applied to communication technology and data mining technology.

Description

Method, system, device and storage medium for identifying terminal model
Technical Field
The present invention relates to communication technologies and data mining technologies, and in particular, to a method, a system, an apparatus, and a storage medium for identifying a terminal model.
Background
Along with the increasing abundance of the number and types of the terminals accessing to the mobile network and the popularization of the Internet of things and the 5G network, the terminal identification in the prior art cannot accurately identify the terminal type corresponding to the IMEI, and has the defect of poor identification accuracy and applicability. In the prior art, two recognition modes mainly exist, and the first mode is as follows: the IMEI of the mobile phone and the model of the mobile phone terminal acquired by the carrier APP, the carrier S1U core network and the carrier business hall are mutually checked to acquire the corresponding relation between the IMEI and the model of the terminal, but the method has large limitation, and the terminal cannot be identified if the carrier APP is not installed or the terminal is not opened in the business hall. The second mode is as follows: comparing the corresponding relation between the mobile phone number and the user reported by the WAP gateway and the IMSI number, IMEI and terminal brand of the user in the network server, checking whether the mobile phone number and the user reported by the WAP gateway are consistent, and because part of terminal IMEI fields are not reported normally, the same TAC (type allocation code) has various terminal types, so that the matching is inconsistent, misjudgment is easy to be caused, and the robustness of the method is poor.
Noun interpretation:
IMEI: the international mobile equipment identification code, namely a mobile phone serial number and a mobile phone serial number, is used for identifying each independent mobile communication device such as a mobile phone in a mobile phone network and is equivalent to an identity card of the mobile phone. Including a Type Assignment Code (TAC), a Serial Number (SNR), etc.
Useagent: the chinese name is user agent, UA for short, which is a special string header that enables the server to identify the operating system and version, CPU type, browser and version, browser rendering engine, browser language, browser plug-in, etc. used by the client.
Disclosure of Invention
In order to solve one of the above technical problems, an object of the present invention is to provide a method, a system, a device and a storage medium for identifying a terminal model of a terminal identification library constructed based on network signaling data.
The technical scheme adopted by the invention is as follows:
a method of identifying a model of a terminal, comprising the steps of:
acquiring a type allocation code of a terminal;
acquiring model information of the terminal according to the type distribution code and a terminal identification library, and identifying the model of the terminal;
the terminal identification library is constructed and obtained based on network signaling data.
Further, the method also comprises the step of establishing the terminal identification library:
acquiring network signaling data of an Internet of things number, and acquiring a plurality of user plane tickets and a plurality of control plane tickets according to the network signaling data, wherein the user plane tickets comprise Http tickets;
extracting corresponding table information based on each Http ticket, wherein the corresponding table information comprises the type allocation codes, terminal models and network system information;
acquiring a unique terminal network access model matched with the type distribution code according to the corresponding table information, and acquiring unique network system information matched with the type distribution code;
and acquiring terminal parameter information according to the terminal network access model, and establishing and acquiring a terminal identification library according to the type distribution code, the unique network system information and the terminal parameter information.
Further, the network signaling data includes 2G network signaling data, 3G network signaling data, 4G network signaling data, and 5G network signaling data.
Further, the extracting the mapping table information based on each Http ticket includes:
acquiring the type allocation code from the Http ticket, and acquiring network system information according to the network system of the Http ticket;
extracting a user field from the Http ticket according to the user characteristics, and acquiring a terminal model according to the user field;
extracting a URL field from the Http ticket according to the URL characteristics, and acquiring a terminal brand according to the URL field;
and obtaining the corresponding table information according to the type distribution code, the network system information, the terminal model and the terminal brand.
Further, obtaining the unique terminal network access model matched with the type distribution code according to the correspondence table information, including:
acquiring a first confidence coefficient of the type allocation code matched with the terminal model according to the corresponding table information and the Http ticket;
acquiring a second confidence coefficient of the type allocation code matched with the terminal model according to the corresponding table information and the control surface ticket;
and acquiring comprehensive confidence coefficient according to the first confidence coefficient and the second confidence coefficient, and acquiring the unique terminal network access model matched with the type allocation code according to the comprehensive confidence coefficient.
Further, obtaining the unique terminal network access model matched with the type distribution code according to the correspondence table information, including:
acquiring a first confidence coefficient of the type allocation code matched with the terminal model according to the corresponding table information and the Http ticket;
acquiring a second confidence coefficient of the type allocation code matched with the terminal model according to the corresponding table information and the control surface ticket;
and acquiring comprehensive confidence coefficient according to the first confidence coefficient and the second confidence coefficient, and acquiring the unique terminal network access model matched with the type allocation code according to the comprehensive confidence coefficient.
Further, the obtaining terminal parameter information according to the terminal network access model includes:
and acquiring terminal parameter information corresponding to the terminal network access model by adopting a web crawler mode, wherein the terminal parameter information comprises a terminal brand, a terminal market model and a terminal type.
Further, the method also comprises the following steps:
and when a plurality of terminal parameter information is obtained according to the terminal network access model, acquiring final terminal parameter information by combining the URL characteristics.
The invention adopts another technical scheme that:
a system for identifying a model of a terminal, comprising:
the data acquisition module is used for acquiring the type allocation code of the terminal;
the model identification module is used for acquiring the model information of the terminal according to the type distribution code and the terminal identification library so as to realize the identification of the model of the terminal;
the terminal identification library is constructed and obtained based on network signaling data.
The invention adopts another technical scheme that:
an apparatus for identifying a model of a terminal, comprising:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement the method described above.
The invention adopts another technical scheme that:
a storage medium having stored therein processor executable instructions which when executed by a processor are for performing the method as described above.
The beneficial effects of the invention are as follows: according to the invention, the terminal identification feature library is constructed by adopting network signaling data, so that the identification type distribution code corresponds to the terminal model, most terminals of the Internet of things accessing to the Internet can be identified, and the terminal identification coverage rate is high.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description is made with reference to the accompanying drawings of the embodiments of the present invention or the related technical solutions in the prior art, and it should be understood that the drawings in the following description are only for convenience and clarity of describing some embodiments in the technical solutions of the present invention, and other drawings may be obtained according to these drawings without the need of inventive labor for those skilled in the art.
FIG. 1 is a flowchart of steps of a method for identifying a model of a terminal in an embodiment of the present invention;
FIG. 2 is a block diagram of a system for identifying a model of a terminal in an embodiment of the present invention;
fig. 3 is a schematic flow chart of performing terminal identification verification in the embodiment of the invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
In the description of the present invention, it should be understood that references to orientation descriptions such as upper, lower, front, rear, left, right, etc. are based on the orientation or positional relationship shown in the drawings, are merely for convenience of description of the present invention and to simplify the description, and do not indicate or imply that the apparatus or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be construed as limiting the present invention.
In the description of the present invention, a number means one or more, a number means two or more, and greater than, less than, exceeding, etc. are understood to not include the present number, and above, below, within, etc. are understood to include the present number. The description of the first and second is for the purpose of distinguishing between technical features only and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, unless explicitly defined otherwise, terms such as arrangement, installation, connection, etc. should be construed broadly and the specific meaning of the terms in the present invention can be reasonably determined by a person skilled in the art in combination with the specific contents of the technical scheme.
As shown in fig. 1, the present embodiment provides a method for identifying a terminal model, including, but not limited to, the following steps:
s1, acquiring a type allocation code (namely TAC) of a terminal;
s2, acquiring model information of the terminal according to the type distribution code and the terminal identification library, and identifying the model of the terminal. The terminal identification library is constructed and obtained based on network signaling data.
Wherein, the terminal identification library is established through the following steps A1-A4:
a1, acquiring network signaling data of the number of the Internet of things, and acquiring a plurality of user plane tickets and a plurality of control plane tickets according to the network signaling data, wherein the user plane tickets comprise Http tickets.
The step is used for acquiring network signaling data of the user number of the Internet of things, and can be acquired by any networking terminal, including Internet of things equipment such as mobile phones, intelligent watches, flat panels, television boxes and the like, but is not limited to intelligent mobile phones. The network signaling data includes 2G network signaling data, 3G network signaling data, 4G network signaling data, and 5G network signaling data. Encoding and decoding the original signaling to generate a corresponding user plane ticket and a control plane ticket, for example, encoding and decoding 2G network signaling data to obtain the user plane ticket and the control plane ticket of the 2G signaling; and encoding and decoding the 5G network signaling data to obtain the user plane and the control plane ticket of the 5G signaling. The control plane ticket is as follows: the user logs on a detailed ticket of all control signaling; the Http ticket is: the user logs on to the detailed ticket for all signaling of HTTP traffic.
A2, extracting corresponding table information based on each Http ticket, wherein the corresponding table information comprises type allocation codes, terminal models and network system information.
This step is used to extract the terminal model. Based on the Http ticket (including 2, 3, 4, 5GHTTP ticket) of each user, using the user feature regular expression in the mobile terminal feature library to match the user field in the ticket, using the URL feature regular expression to match the URL field in the ticket, extracting the mobile terminal brand and model contained in the Http message header. For example, the characteristics of the useagent of the OPPO A7 terminal in the mobile terminal characteristics library are shown in table 1:
TABLE 1
Branding Model number Feature type Rules of
OPPO A7 Useragent feature *PBFM00*
The user field value in the ticket is as follows:
Dalvik％2F2.1.0+％28Linux％3B+U％3B+Android+8.1.0％3B+PBFM00+Build％2FOPM1.171019.026％29
and matching with PBFM00 of the user characteristic rule of OPPO A7, wherein the successful matching indicates that the record is reported by the OPPO A7 terminal. The URL rules are the same and are not described in detail herein.
Finally, a corresponding table (i.e. corresponding table information) of the TAC and the brand and model of the terminal is generated according to the obtained user field, URL field and the like, and the specific information content is shown in the following table 2:
TABLE 2
Sequence number Fields Remarks
1 Number of number
2 TAC First 8 bits of IMEI
3 Terminal brand Using canonical extraction in URLs
4 Terminal model Regular extraction in USERAGENT
5 Telephone bill network system 2/3/4/5G
A3, acquiring the unique terminal network access model matched with the type distribution code according to the corresponding table information, and acquiring the unique network system information matched with the type distribution code.
The step is used for verifying the information such as the model and the brand obtained in the step A2, so that the recognition accuracy is improved. Based on the extracted corresponding table (i.e. corresponding table information) of the TAC and the user, the unique terminal model corresponding to the TAC is identified through the established discrimination logic, the unique network system is identified, and the confidence is output. Referring to fig. 3, the identification verification logic is specifically as follows:
1) Judging the network system of the terminal model: taking the highest network system of the model as the maximum supporting network system of the terminal model (if a certain model is simultaneously presented in a 2/3/4/5G Http ticket, judging that the model is a 5G terminal), and specifically judging conditions are as follows:
a) 5G terminal: the terminal model appears in the 5G ticket;
b) 4G terminal: the terminal model appears on the 4G ticket and does not appear on the 5G ticket;
c) 3G terminal: the terminal model appears on the 3G ticket and does not appear on the 4/5G ticket;
d) 2G terminal: the terminal model only appears on the 2G ticket.
2) TAC corresponds to the terminal model confidence level: based on HTTP ticket and control surface ticket, counting, outputting 3 confidence degrees, setting weight of each confidence degree based on Defeier method, carrying out weighted summation, obtaining comprehensive confidence degrees of each TAC corresponding to each terminal model, selecting the terminal model of the TAC corresponding to the confidence degree TOP1 as the terminal model corresponding to the TAC (namely, when a certain TAC corresponds to a plurality of terminal models, respectively calculating the comprehensive confidence degrees of the TAC corresponding to the plurality of terminal models, and obtaining the terminal model with the highest comprehensive confidence degree (namely, the confidence degree TOP 1) as the unique terminal model corresponding to the TAC). The definition and calculation modes of each confidence coefficient are as follows:
a) HTTP ticket confidence: and defining the number of the terminals with the model number in the HTTP traffic of the maximum supported network system of the terminal corresponding to the TAC. The purpose is to reflect the model ratio in the normal user surfing behavior, for example, TAC= 48694550, and the HTTP ticket confidence coefficient corresponding to the networking model HRY-AL00Ta (4G terminal) is calculated as follows:
b) Control plane ticket confidence: and defining the ratio of the number of the terminals with the model in the HTTP traffic of the maximum supported network system of the corresponding terminal of the TAC to the total number of the control surface ticket terminals of the whole network section of the TAC 2/3/4/5G. The aim is to reflect whether the TAC has the condition that equipment reports IMEI in an irregular manner, and partial Internet of things equipment and the mountain village have the condition that the IMEI is reported in an irregular manner, so that the control plane ticket confidence of the TAC section is lower. For tac= 48694550, the control plane ticket confidence corresponding to the access model HRY-AL00Ta (4G terminal) is calculated as follows:
c) Comprehensive confidence: and (3) carrying out weighted summation on the HTTP ticket confidence coefficient of a certain terminal model and the control surface ticket confidence coefficient corresponding to a certain TAC, wherein each confidence coefficient weight is set by a Defeil method, and the value range of the comprehensive confidence coefficient is controlled to be 0 percent and 100 percent. The calculation method is as follows:
comprehensive confidence = w1 x HTTP ticket confidence + w2 x control plane ticket confidence
Terminal identification and verification result table: selecting the terminal model of which the comprehensive confidence coefficient is larger than a set threshold and corresponds to the confidence coefficient TOP1 as the terminal network access model corresponding to the TAC, wherein the specific content is as shown in the following table 3:
TABLE 3 Table 3
And A4, acquiring terminal parameter information according to the network access model of the terminal, and establishing and acquiring a terminal identification library according to the type distribution code, the unique network system information and the terminal parameter information.
After the step A3, the same TAC corresponds to a unique terminal network access model and a unique terminal network system, and in step A4, terminal parameter information corresponding to the unique terminal network access model needs to be obtained according to the unique terminal network access model. Based on the identified terminal network access model, using the web crawler to translate information such as product model, brand, terminal type and the like corresponding to the terminal network access model, and finally constructing a mobile terminal identification library. When the terminal network-access model climbs to a plurality of corresponding brand terminals, the crawler translation is carried out by combining the terminal brands identified by the URL features in the terminal model extraction module and using the double dimensions of the network-access model and the brand, and the terminal model corresponding to the TAC is determined. Specific fields are shown in table 4 below:
TABLE 4 Table 4
Sequence number Fields Remarks
1 TAC First 8 bits of IMEI
2 Terminal brand Apple, hua Cheng, millet, etc
3 Terminal market model Such as iPhone XR
4 Terminal network access model Such as iPhone118
5 Terminal network system 2G、3G、4G、5G
6 Terminal operating system IOS, android, etc
7 Device type Mobile phone, intelligent watch, tablet, internet of things equipment and the like
After the terminal identification library is established through the steps A1-A4, when the IMEI or the TAC of any terminal is obtained, the corresponding terminal model can be searched through the terminal identification library.
In summary, compared with the prior art, the method of the embodiment has at least the following advantages:
(1) The embodiment is suitable for identifying the full-type mobile terminal of the 2/3/4/5G full network segment, can identify the terminal types of the mobile phone, the intelligent watch, the television box, the tablet, the internet of things terminal and other access networks, and effectively makes up the defect of narrower identification range of the existing method.
(2) Performing TAC and terminal model accuracy verification by combining user plane data and control plane data, and effectively improving recognition accuracy and robustness; and calculating the comprehensive confidence coefficient of the corresponding relation between the TAC and the terminal model, and effectively making up the defect of low accuracy of checking the terminal model by the existing method.
(3) And information of a product model, a brand, a terminal type and the like corresponding to the network access model of the terminal is translated based on information extracted by the user agent and the URL in two dimensions, so that the situation that the terminal identification accuracy is low when multiple brands use the same network access model code at the same time is effectively improved.
As shown in fig. 2, this embodiment further provides a system for identifying a terminal model, including:
the data acquisition module is used for acquiring the type allocation code of the terminal;
the model identification module is used for acquiring model information of the terminal according to the type distribution code and the terminal identification library and realizing identification of the model of the terminal;
the terminal identification library is constructed and obtained based on network signaling data.
The system for identifying the terminal model can execute the method for identifying the terminal model provided by the embodiment of the method, can execute any combination implementation steps of the embodiment of the method, and has the corresponding functions and beneficial effects of the method.
The embodiment also provides a device for identifying the terminal model, which comprises:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement the method described above.
The device for identifying the terminal model can execute the method for identifying the terminal model provided by the embodiment of the method, can execute any combination implementation steps of the embodiment of the method, and has the corresponding functions and beneficial effects of the method.
The present embodiment also provides a storage medium having stored therein processor-executable instructions which, when executed by a processor, are for performing the method as described above.
The embodiment also provides a storage medium which stores instructions or programs for executing the method for identifying the terminal model provided by the embodiment of the method, and when the instructions or programs are run, any combination of the embodiments of the executable method can implement steps, and the method has corresponding functions and beneficial effects.
It is to be understood that all or some of the steps, systems, and methods disclosed above may be implemented in software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of one of ordinary skill in the art without departing from the spirit of the present invention.

Claims (8)

1. A method for identifying a model of a terminal, comprising the steps of:
acquiring a type allocation code of a terminal;
acquiring the terminal market model of the terminal according to the type distribution code and the terminal identification library, and identifying the terminal market model;
the terminal identification library is constructed and obtained based on network signaling data;
the method further comprises the step of establishing the terminal identification library:
acquiring network signaling data of an Internet of things number, and acquiring a plurality of user plane tickets and a plurality of control plane tickets according to the network signaling data, wherein the user plane tickets comprise Http tickets;
extracting corresponding table information based on each Http ticket, wherein the corresponding table information comprises the type allocation codes, terminal network access model numbers and network system information;
acquiring a unique terminal network access model matched with the type distribution code according to the corresponding table information, and acquiring unique network system information matched with the type distribution code;
acquiring terminal parameter information according to the terminal network access model, and establishing and acquiring a terminal identification library according to the type distribution code, the unique network system information and the terminal parameter information; the terminal parameter information comprises a terminal brand, a terminal market model and a terminal type;
the obtaining the unique terminal network access model matched with the type distribution code according to the corresponding table information comprises the following steps:
acquiring a first confidence coefficient of matching the type allocation code with the network access model of the terminal according to the corresponding table information and the Http ticket;
acquiring a second confidence coefficient of matching the type distribution code with the network access model of the terminal according to the corresponding table information and the control surface ticket;
and acquiring comprehensive confidence coefficient according to the first confidence coefficient and the second confidence coefficient, and acquiring the unique terminal network access model matched with the type allocation code according to the comprehensive confidence coefficient.
2. The method for identifying a model of a terminal according to claim 1, wherein said extracting correspondence table information based on each of said Http tickets comprises:
acquiring the type allocation code from the Http ticket, and acquiring network system information according to the network system of the Http ticket;
extracting a user field from the Http ticket according to the user characteristics, and acquiring a terminal network access model according to the user field;
extracting a URL field from the Http ticket according to the URL characteristics, and acquiring a terminal brand according to the URL field;
and obtaining the corresponding table information according to the type distribution code, the network system information, the terminal network access model and the terminal brand.
3. The method for identifying a terminal model according to claim 1, wherein the obtaining unique network system information matched with the type allocation code includes:
and acquiring the highest network system from the corresponding table information corresponding to the type allocation code as the unique network system information matched with the type allocation code.
4. The method for identifying a terminal model according to claim 2, wherein the obtaining terminal parameter information according to the terminal access model comprises:
and acquiring terminal parameter information corresponding to the terminal network access model by adopting a web crawler mode.
5. The method for identifying a model of a terminal as in claim 4, further comprising the steps of:
and when a plurality of terminal parameter information is obtained according to the terminal network access model, acquiring final terminal parameter information by combining the URL characteristics.
6. A system for identifying a model of a terminal, comprising:
the data acquisition module is used for acquiring the type allocation code of the terminal;
the model identification module is used for acquiring the terminal market model of the terminal according to the type distribution code and the terminal identification library, so as to realize the identification of the terminal market model;
the terminal identification library is constructed and obtained based on network signaling data;
the terminal identification library is characterized by further comprising a module for establishing the terminal identification library, and the module is specifically used for:
acquiring network signaling data of an Internet of things number, and acquiring a plurality of user plane tickets and a plurality of control plane tickets according to the network signaling data, wherein the user plane tickets comprise Http tickets;
extracting corresponding table information based on each Http ticket, wherein the corresponding table information comprises the type allocation codes, terminal network access model numbers and network system information;
acquiring a unique terminal network access model matched with the type distribution code according to the corresponding table information, and acquiring unique network system information matched with the type distribution code;
acquiring terminal parameter information according to the terminal network access model, and establishing and acquiring a terminal identification library according to the type distribution code, the unique network system information and the terminal parameter information; the terminal parameter information comprises a terminal brand, a terminal market model and a terminal type;
the obtaining the unique terminal network access model matched with the type distribution code according to the corresponding table information comprises the following steps:
acquiring a first confidence coefficient of matching the type allocation code with the network access model of the terminal according to the corresponding table information and the Http ticket;
acquiring a second confidence coefficient of matching the type distribution code with the network access model of the terminal according to the corresponding table information and the control surface ticket;
and acquiring comprehensive confidence coefficient according to the first confidence coefficient and the second confidence coefficient, and acquiring the unique terminal network access model matched with the type allocation code according to the comprehensive confidence coefficient.
7. An apparatus for identifying a model of a terminal, comprising:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement a method of identifying a model of a terminal as claimed in any one of claims 1 to 5.
8. A storage medium having stored therein a processor executable program, which when executed by a processor is adapted to carry out the method of any one of claims 1-5.
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