CN106294219B - Equipment identification and data processing method, device and system - Google Patents
Equipment identification and data processing method, device and system Download PDFInfo
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- CN106294219B CN106294219B CN201510276204.2A CN201510276204A CN106294219B CN 106294219 B CN106294219 B CN 106294219B CN 201510276204 A CN201510276204 A CN 201510276204A CN 106294219 B CN106294219 B CN 106294219B
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F13/00—Interconnection of, or transfer of information or other signals between, memories, input/output devices or central processing units
- G06F13/10—Program control for peripheral devices
- G06F13/102—Program control for peripheral devices where the programme performs an interfacing function, e.g. device driver
Abstract
The application provides a method, a device and a system for equipment identification and data processing. The device identification method may include: acquiring attribute data including parameter information of a designated application in target equipment according to set configuration information; comparing the acquired attribute data with stored equipment attribute data, and searching the stored equipment attribute data matched with the acquired attribute data; and identifying the equipment corresponding to the acquired attribute data according to the query result. By utilizing the embodiments in the application, the equipment can be identified through the collected software information in the equipment, and the equipment can be identified when the hardware information of the equipment cannot meet the identification requirement of the equipment.
Description
Technology neighborhood
The application belongs to the field of computer information processing, and particularly relates to a method and a device for equipment identification and data processing.
Background
With the development of information technology, different electronic terminal devices can be interconnected and communicated in various ways, so that data content sharing or application, hardware control and the like are realized, and the convenience and comfort of life, work and entertainment of people are greatly improved.
Generally, before the terminal device establishes communication, the terminal device needs to be identified, and the terminal device needing to be operated is determined to be legal. The current method mainly adopted in terminal equipment identification includes identification through relevant information of physical hardware equipment. For example, when a PC (Personal Computer) device is identified, the identification may be performed mainly by using hardware unique identification information on the PC device, such as device information such as a MAC address of a network card, a hard disk serial number, and a BIOS.
Generally, devices generally used include device information for identifying hardware, such as a model number and a serial number of a device product. However, in the terminal market, more and more manufacturers have irregular device information names, and the emulational device uses the regular device hardware information or uses a certain tool to modify the device information, so that the device cannot be identified or is identified incorrectly. In some practical application scenarios, hardware information of some devices is difficult to, even impossible to collect, or poses a threat to personal safety, such as deep-sea device information or high-risk PC device information detection. In addition, in other application scenarios, due to legal level constraints, the possibility of acquiring device hardware information is also becoming less and less.
Due to the objective problems, the application range of the method for identifying the equipment through the hardware information of the equipment in the prior art is smaller and smaller, and the requirement for equipment identification cannot be met in some application scenes.
Disclosure of Invention
The application aims to provide a method, a device and a system for equipment identification and data processing, which can identify equipment through collected software information in the equipment and realize the identification of the equipment when hardware information of the equipment cannot meet the identification requirement of the equipment.
The method, the device and the system for equipment identification and data processing are realized as follows:
a method of device data processing, the method comprising:
acquiring attribute data including parameter information of a designated application in target equipment according to the set configuration information;
performing dimensionality reduction on the acquired attribute data to acquire the attribute data subjected to dimensionality reduction;
and storing the attribute data after the dimension reduction processing based on the equipment to which the attribute data belongs.
A device identification method, the method comprising:
acquiring attribute data including parameter information of a designated application in target equipment according to set configuration information;
comparing the acquired attribute data with stored equipment attribute data, and searching the stored equipment attribute data matched with the acquired attribute data;
and identifying the equipment corresponding to the acquired attribute data according to the query result.
An apparatus for device data processing, the apparatus comprising:
the data acquisition module is used for acquiring attribute data of the target equipment including the parameter information of the designated application according to the stored configuration information;
the data processing module is used for carrying out dimensionality reduction on the acquired attribute data and acquiring the attribute data subjected to dimensionality reduction;
and the storage module is used for storing the attribute data after the dimension reduction processing based on the equipment to which the attribute data belongs.
An apparatus for device identification, the apparatus comprising:
the first data acquisition module is used for acquiring attribute data of the target equipment including the parameter information of the designated application according to the set configuration information;
the first data processing module is used for comparing the acquired attribute data with stored equipment attribute data and searching the stored equipment attribute data matched with the acquired attribute data;
and the equipment identification module is used for identifying the equipment corresponding to the acquired attribute data according to the query result.
A device identification system, the system configured to, comprising:
the storage unit is used for storing the acquired attribute data of the equipment, including the software information of the equipment;
the processing unit is used for acquiring attribute data to be processed of the target equipment, wherein the attribute data to be processed comprises the target equipment software information; and the attribute data to be processed is matched with the attribute data stored in the storage unit, and the target equipment is identified according to the matching result.
The method, the device and the system for equipment identification and data processing can be used for collecting attribute data of target equipment, wherein the attribute data can comprise parameter information of specified application in the equipment. The specific application may include one or more preset software applications to be collected in the target device, such as a browser, a navigation application, a shopping client application, and the like. In this way, the collected attribute data includes information of software parameters in the device, and the device can be identified by using the software parameter information in the device. In the application, the acquired attribute data of the target device can be compared with the stored device attribute data which also comprises device software parameter information, and the stored device attribute data matched with the target device can be found. Then, the device corresponding to the matched stored device attribute data can be judged according to a preset identification rule, so as to realize the identification of the target device. The method and the device for identifying the equipment can quickly and reliably identify the equipment through software information in the equipment.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.
FIG. 1 is a schematic flow chart diagram illustrating an embodiment of a method for device identification according to the present application;
FIG. 2 is a flow chart of a method of another embodiment of a device identification method described herein;
FIG. 3 is a flow chart of a method of another embodiment of a device identification method described herein;
FIG. 4 is a flow chart of a method of another embodiment of a device identification method described herein;
FIG. 5 is a flow chart of a method of one embodiment of a device data processing method described herein;
FIG. 6 is a flow chart of a method of another embodiment of a method of device data processing as described herein;
FIG. 7 is a flow chart of a method of another embodiment of a method of device data processing as described herein;
FIG. 8 is a flow chart of a method of another embodiment of a method of device data processing as described herein;
FIG. 9 is a flow chart of a method of another embodiment of a method of device data processing as described herein;
FIG. 10 is a block diagram of an embodiment of an apparatus data processing device according to the present application;
FIG. 11 is a block diagram of another embodiment of an apparatus data processing device according to the present application;
FIG. 12 is a block diagram of another embodiment of an apparatus data processing device according to the present application;
FIG. 13 is a block diagram of another embodiment of an apparatus data processing device according to the present application;
FIG. 14 is a block diagram of an embodiment of an apparatus identification device according to the present application;
fig. 15 is a schematic block diagram of an embodiment of a device identification module in the device identification apparatus according to the present application.
Detailed Description
In order to make the technical solutions in the present application better understood by those in the technical field of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without any creative effort shall fall within the protection scope of the present application.
The following describes the method for identifying a drawing body according to the present application in detail with reference to the drawings. Fig. 1 is a flowchart of a method of an embodiment of a device identification method according to the present application. Although the method steps are provided in the present application as described in the following examples or flowcharts, more or fewer steps may be included in the method based on conventional or non-inventive efforts. In the case of steps where no necessary causal relationship exists logically, the order of execution of the steps is not limited to that provided by the embodiments of the present application. When the method is executed in an actual device or end product, the method can be executed sequentially or in parallel according to the embodiment or the method shown in the figure (for example, in the environment of a parallel processor or a multi-thread processing).
Specifically, an embodiment of an apparatus identification method provided in the present application is shown in fig. 1, where the method may include:
s1: and acquiring attribute data including parameter information of the appointed application in the target equipment according to the set configuration information.
The devices described in this application may include electronic devices of various terminals, such as PC terminals (notebook, desktop), mobile communication terminals, PDAs, web servers, sensing devices, transmission devices, relay devices, and the like. The device generally comprises a physical hardware structure and corresponding data processing and control software. The method described in the present application can be specifically described by taking a PC terminal device as an example.
Generally, one or more types of software are installed in the PC terminal device, and specifically, the software may include a terminal service application, a service system, signal receiving and transmitting control, data processing, data storage, information display, and the like. The software installed in the device may be collectively referred to as an application in the present application, and the specific application described in this embodiment may include, but is not limited to, an instant messaging tool, a page information browser, a video player, data acquisition processing software, an information display tool, and the like in a PC terminal device. The application in the device usually contains parameter information of the application, such as name and version information of instant messaging software, or type of browser, installed plug-in, whether cookie is opened, flash version, and the like. The method and the device for acquiring the parameter information of the designated application can be used for presetting the designated application to be acquired by the device, acquiring the configuration information of the parameter information of the designated application, and taking the acquired parameter information including the designated application as the attribute data of the device after acquiring the parameter information of the designated application.
Of course, which parameter information of the specific application needs to be collected can be preset according to different applications. For example, the target device in this embodiment is a PC terminal device, the specified application includes a browser of the PC terminal device, and the obtained attribute data in this embodiment may include information of the browser on the PC terminal device when the browser makes an http request, screen information, webrtc information, canvas information based on the html5 technology, installed plug-in and plug-in font list, language, information related to video flash, login IP, and a browser (such as MSIE, Chrome, and Firefox) used. The embodiment collects and acquires the parameter information of the browser application in the target device, and generally can cover the configuration information when the user surfs the internet through the browser application.
And acquiring attribute data including parameter information of the appointed application in the target equipment according to the set configuration information. It should be noted that the attribute data may include parameter information of the specified application, and in other application scenarios, the attribute data may also include information of hardware of the device, such as a serial number of the device, a network card, a serial number of a hard disk, and the like.
S2: and comparing the acquired attribute data with stored equipment attribute data, and searching the stored equipment attribute data matched with the acquired attribute data.
After acquiring and acquiring the attribute data of the target device including the parameters of the designated application, the attribute data of the target device may be compared with the stored device attribute data, and whether device attribute data matched with the attribute data of the target device exists or not may be searched in the stored device attribute data. The stored device attribute data in this embodiment may include device attribute data including parameter information applied in the device, which is collected and stored in the manner described in S1.
The parameter information of the specified application in the device in this embodiment may also be represented as information of the specified application in different dimensions, for example, the parameter information a1 and a2 of the specified application a may be represented as parameter information of the specified application as a browser application: browser type and version, and plug-in information installed in the browser. Of course, the format of the stored device attribute data or the dimension (type) of the parameter information of the specific application is the same as the collected attribute data of the target device, or part of the attribute data may be the same. For example, the stored device attribute data includes parameter information D _ a1, D _ a2, D _ A3, D _ B1, D _ B2, D _ B3, D _ B4, D _ C1, and D _ C2 of the device D1 specifying the application A, B, C, and the parameter information D _ a1, …, and D _ C2 may correspond to specific attribute data values. The designated application C may not be installed in the target device T, and the parameter information B4 is included in the designated application B in the target device T. Therefore, in the application scenario, the application-specific parameter information included in the acquired attribute data of the target device T may be T _ a1, T _ a2, T _ A3, T _ B1, T _ B2, and T _ B3.
The obtained attribute data of the target device may then be compared with stored device attribute data to find stored device attribute data that matches the obtained attribute data. Specifically, the searching for the stored device attribute data matched with the acquired attribute data mainly includes:
and searching all the acquired attribute data of the target equipment or equipment attribute data with the same part of attribute data in the stored equipment attribute data.
In practical application of the present application, the stored software information of the terminal device may include tens, hundreds, or even more information, and a few parameter information may be taken as an example for description in the present application. For example, 6 pieces of parameter information T _ a1, T _ a2, T _ A3, T _ B1, T _ B2, and T _ B3 of the acquired target device T are queried, the device attribute data of the device D1 including all pieces of parameter information in the acquired target device T may be queried in the stored device attribute data, and the values of the parameter information in the corresponding dimensions of the device D1 and the target device T are equal, so that the device attribute data of the device D1 may be used as the device attribute data matching the acquired attribute data.
The device attribute data stored in the present application may include a logical body as a storage unit to store the device attribute data, or may also be a functional module on a server, or a specific database, or a specific entity as a storage unit to store the setting attribute data. In other embodiments, the device attribute data may be stored in a distributed manner in which the data is stored in different servers or databases.
It should be noted that, in some application scenarios, the device identification method described in the present application may perform some processing, such as format conversion, mapping, dimension reduction, etc., on the acquired attribute data after acquiring the attribute data, so that the attribute data meets the data processing requirements of subsequent data search, judgment, etc.
And comparing the attribute data of the acquired target equipment with stored equipment attribute data, and searching equipment attribute data matched with the acquired attribute data.
S3: and identifying the equipment corresponding to the acquired attribute data according to the query result.
And identifying the equipment corresponding to the acquired attribute data according to the query result of querying the attribute data of the target equipment in the stored equipment attribute data. For example, the device corresponding to the storage device data that includes all the parameter information in the acquired attribute data and has the same value of parameter information is used as the device corresponding to the acquired data.
Of course, the specific identification method for identifying the device corresponding to the acquired attribute data according to the query result can be used for carrying out the device according to specific data processing requirements. When facing different devices and different application attribute data, different identification methods of the devices can be adopted. In another embodiment of the present application, a method for identifying a device corresponding to the attribute data according to the query result may be provided. Fig. 2 is a flowchart of a method according to another embodiment of the device identification method in the present application, and as shown in fig. 2, specifically, the identifying, according to the query result, the device corresponding to the obtained attribute data may include:
s301: and when the stored equipment attribute data matched with the acquired attribute data is found, taking the equipment corresponding to the equipment attribute data which meets the requirements of the same number and the maximum number and/or the preset percentage of the values of the acquired attribute data as the equipment corresponding to the acquired attribute data.
In a specific application scenario, for example, the device attribute data of the three devices D1, D2, and D3 are found in the stored device attribute data to match the obtained attribute data. At this time, the number of the three matched device attribute data that is the same as the number of the obtained attribute data may be compared, and then the device corresponding to the device attribute data that meets the preset matching requirement may be used as the device for identifying the obtained attribute data. The matching requirement may be set according to a requirement, for example, the number of the obtained attribute data that is the same as the value of the matched device attribute data may be set to be the largest, or the number of the obtained attribute data and the matched device attribute data may reach a predetermined percentage (e.g., 99%). Of course, the matching requirement may also be set by a plurality of conditions, for example, the maximum number of the same device attribute data is selected from the predetermined percentage (e.g. 95%) of the same format. Therefore, the equipment is identified under the condition that the same number of the values of the attribute data meets certain matching requirements, and the equipment identification accuracy of the method can be improved.
In some application scenarios, if multiple PC terminal devices use multiple identical applications, many parameter information in these identical applications are often identical. In order to further improve the accuracy of device identification, the method for identifying the device based on the software information in the device may set a corresponding weight value for the applied parameter information in the stored or acquired device attribute data in advance, and further calculate and identify the device according to the set weight value. Fig. 3 is a flowchart of a method of another embodiment of the device identification method according to the present application, and as shown in fig. 3, in another embodiment of the device identification method according to the present application, the identifying a device corresponding to the obtained attribute data according to the query result may include:
s302: when the stored equipment attribute data matched with the acquired attribute data is found, calculating an equipment score corresponding to the equipment attribute data according to the set weight value of the parameter information in the matched equipment attribute data; and taking the equipment corresponding to the equipment attribute data with the equipment score reaching the preset requirement as the equipment corresponding to the acquired attribute data.
Specifically, for example, when the specified application includes a browser of page information, different devices may include the same browser, and at this time, it is difficult to distinguish the different devices from each other by the browser name in the parameter information of the browser. Because the same browser may have different versions among different devices due to the use habit of the user, or different plug-ins installed in the browser, or different attribute font lists used by the browser, different weight values may be set for different parameter information in this embodiment, and the device may be identified more accurately according to the attribute data. If the weight value of the parameter information for the browser name is set to be low, the weight value of the parameter information of the plug-in and the plug-in version installed in the browser is set to be high. The device score may be calculated from the weight value of the parameter information and the data value of itself. In this embodiment, a predetermined requirement for the device score may be set, and the device corresponding to the acquired attribute data may be determined according to the predetermined requirement. For example, the same parameter information as the target device in each dimension may be calculated to obtain a corresponding score, the scores of the parameter information of multiple dimensions may be summarized to form a score of a device corresponding to the stored device attribute data, and a device corresponding to the device attribute data with the highest device score may be used as the device corresponding to the acquired attribute data.
In another embodiment of the device identification method according to the present application, when the query result does not satisfy a preset identification condition, the target device corresponding to the acquired attribute data is identified as a new device. Specifically, if the stored device attribute data matched with the acquired attribute data is not found in the stored device attribute data, or the corresponding matching requirement is not satisfied, the target device corresponding to the acquired attribute data may be identified as a new device. Fig. 4 is a flowchart of a method according to another embodiment of the device identification method described in the present application, and as shown in fig. 4, the device identification method described in the present application may further include:
s4: identifying the target device corresponding to the acquired attribute data as a new device when at least one of the following is satisfied:
the stored device attribute data matched with the acquired attribute data is not found in the stored device attribute data;
the stored device attribute data does not meet the requirement that the same number of values as the obtained attribute data is the most and/or reaches a predetermined percentage;
the device score of the stored device attribute data does not meet the predetermined requirement.
In this embodiment, if the device corresponding to the acquired attribute data is not identified according to the stored device attribute data, the target device of the acquired attribute data may be regarded as a new device. Of course, the attribute data of the identified new device may be further stored in a corresponding database, which may be used for subsequent device identification information.
The device identification method provided by the application can be used for identifying the device by using software information included in the device, and a new device identification method is provided. When the hardware equipment information is difficult to acquire, dangerous and even impossible to acquire, the equipment software information-based equipment identification can be effectively realized, and the effective and reliable identification of the terminal equipment is realized.
In the actual acquisition of attribute data of terminal equipment, a huge number of devices are often faced, and these devices often include a large amount of application software, so that a large amount of attribute data of the devices are also generated. Based on the idea of identifying the equipment by using the software information of the equipment, the application can further analyze and process the data after the equipment attribute data of different equipment in the process of collecting and storing the equipment attribute data, optimize data storage, and improve the data processing speed when inquiring and searching the equipment attribute data. Therefore, the present application further provides an apparatus data processing method, and fig. 5 is a flowchart of a method according to an embodiment of the apparatus data processing method described in the present application, and as shown in fig. 5, a specific method may include:
s11: acquiring attribute data including parameter information of a designated application in target equipment according to the set configuration information;
s22: performing dimensionality reduction on the acquired attribute data to acquire the attribute data subjected to dimensionality reduction;
s33: and storing the attribute data after the dimension reduction processing based on the equipment to which the attribute data belongs.
In this embodiment, configuration information of which parameter information of which applications in the device need to be acquired may be preset, and then attribute data in the target device may be acquired according to the configuration information. After acquiring and acquiring the attribute data of the target device, the attribute data may be analyzed first, for example, the information obtained by classifying and counting the attribute data may be used to acquire the distinguishing degree between different devices, which parameter information is mainly reflected in, or how much of the set attribute data to be acquired is acquired in the actual acquisition process, and so on. And adopting a corresponding dimension reduction processing method according to the analysis result of the acquired attribute data. The data dimension reduction processing described in the present application may generally include performing feature extraction, such as integration, transformation, clustering, extraction, etc., on raw data at a high latitude by using a certain data processing method, and forming a low-dimensional feature vector, such as a map-to-low-latitude basis vector, that may represent the attributes of the main body of the raw data after processing. After the dimension of the attribute data is reduced, the complexity of calculation processing such as subsequent data query can be greatly reduced, and the data query speed is improved.
The specific method for performing the dimension reduction processing on the attribute data can be selected according to the data processing requirement or the characteristics of the attribute data. For example, Principal Component Analysis (PCA), Local Sensitive Hash (LSH), or the like may be used. In a specific application scenario, for example, the device is a PC terminal device, and when the acquired attribute data includes parameter information of a browser of the PC terminal device, a Principal Component Analysis (PCA) method may be used to perform data dimension reduction. The principal component analysis process usually includes finding R new variables, so that the R new variables can reflect the main features of the original data, compressing the size of the original data matrix, and reducing the data dimension, so as to achieve the most important specific of the original data with the least number of bits.
As described above, in the collected attribute data, the degree of importance that different parameter information can be distinguished from one another in different devices may be different. Therefore, in another embodiment of the present application, the device data processing method may further include:
s44: and setting a weighted value for the parameter information of the attribute data after the dimension reduction processing.
Fig. 6 is a flowchart of a method according to an embodiment of the device data processing method in the present application, and as shown in fig. 6, a weight value may be set for the parameter information of the attribute data after the dimension reduction processing according to an analysis result of the collected attribute data. In other application scenarios, the weight value of the parameter information may also be set according to third party statistical data or an empirical value set by itself. Therefore, corresponding weight values are set for different parameter information according to the influence degree of the parameter information on equipment distinguishing, and the equipment can be identified more accurately based on the equipment attribute data.
Fig. 7 is a flowchart of a method of an embodiment of a device data processing method described in the present application, and as shown in fig. 7, in another preferred embodiment of the device data processing method described in the present application, the method may further include:
s441: and calculating the stability of the attribute data, and adjusting the weight value of the parameter information in the attribute data according to the calculation result of the stability.
The stability described in this embodiment generally refers to a value that can indicate the degree of consistency of attribute data on the premise of the same device. For example, a device a collects parameter information including a property font list, and the stability of the property data as the property font list may be a proportional value of the same value collected under the same device. The acquired attribute data in the application is related information of software in equipment, for example, and the information of the software is easy to change in some application scenes such as a mobile communication terminal. In order to effectively measure and judge the possibility that the values of the same attribute data in the same device are different in different acquisition processes, and avoid the situation that the same attribute data are considered to be different devices due to different acquired values of the same attribute data as much as possible, in this embodiment, the stability of the attribute data may be analyzed and calculated according to the acquired attribute data, and then the weight value of the parameter information may be adjusted according to the stability of the attribute data.
The calculation method of the stability of the attribute data can be specifically selected or set according to the data processing requirements or the characteristics of the acquired attribute data. Specifically, for example, the calculating the stability of the attribute data may include calculating, by statistically analyzing the attribute data, a probability that the same attribute data of the same device changes at different collection times. The higher the probability of the change of the calculated attribute data is, the more easily the attribute data is changed, and the worse the stability of the corresponding attribute data is; conversely, the lower the probability of the calculated attribute data being changed, the less likely the attribute data is to be changed, and the higher the stability of the corresponding attribute data.
In different application scenarios, the stability of the attribute data may be calculated in different ways. The calculating the stability of the attribute data comprises at least one of the following modes:
calculating the probability of converting the specified attribute data into another attribute data;
calculating the probability of converting the value of the designated attribute data into another value;
to calculate the probability that the specified attribute data derives another attribute data.
Specifically, the calculating the stability of the attribute data may include calculating a probability that one attribute data is converted into another attribute data, such as a possibility that a device replaces a currently used plug-in. Or the probability of converting one attribute data value into another attribute data value can be calculated, as the version information of the same software changes due to the software version upgrade in the same device. Or the probability that one attribute data is derived from another attribute data can be calculated, like the same device installation plug-in L1, and the probability that the plug-in L2 is probably installed after the device installation plug-in L1 can be calculated according to the collected acquired attribute data statistics. Of course, the stability of the attribute data may be calculated in a variety of ways, including the above or otherwise.
And adjusting the weight value of the parameter information in the attribute data according to the calculation result of the stability, wherein the weight value can be specifically set according to the data processing requirement. The stability of the acquired attribute data can be periodically calculated in a statistical manner, and then the weight value is adjusted according to the calculation result. For example, for attribute data with stability lower than a set minimum threshold, it may indicate that the attribute data changes too frequently, and the effectiveness of distinguishing for device identification decreases, so that the weight value of the attribute data parameter information decreases. Correspondingly, for attribute data with higher stability, the weight value of the parameter information in the attribute data can be correspondingly improved.
Due to the fact that the number of the devices and the software information are constantly changed, the attribute data collection and processing can be optimized and adjusted periodically or regularly according to changes of conditions in practical application, data storage and processing efficiency is improved, and accuracy of device identification is improved.
Fig. 8 is a flowchart of a method of an embodiment of a device data processing method described in the present application, and as shown in fig. 8, in another preferred embodiment of the device data processing method described in the present application, the method may further include:
s55: and calculating the acquisition rate of the attribute data, and updating the configuration information according to the calculation result of the acquisition rate.
For example, a low collection rate of certain parameter information D4 in the calculated attribute data may indicate that the parameter information D4 is difficult to collect in the terminal device, and therefore, the parameter information D4 may not be collected in subsequent data collection of the updated setting in the configuration information. Of course, in some other application scenarios, the configuration information may also be optimized by reducing the acquisition priority of the parameter information whose acquisition rate does not meet the requirement.
According to the embodiment, the collection rate of the attribute data is calculated and analyzed, the collection configuration information is optimized, the software information needing to be collected in the equipment is reasonably set, and the data collection and storage efficiency is improved. Meanwhile, the accuracy of identifying the equipment according to the acquired attribute data is improved.
The embodiment of the device data processing method can analyze, calculate, process, store and the like acquired attribute data including software information in the device, and can provide powerful data information support for device identification in the application. Based on the optimization of the acquisition and storage of the software information of the equipment, the accuracy of equipment identification can be further improved. Of course, in the device data processing method described in the present application, the attribute data of the new device identified in the device identification method described in the present application may be stored. Therefore, in the device data processing method described in the present application, the method may further include:
s66: receiving attribute data identified as a new device, and storing the attribute data of the new device.
Fig. 9 is a flowchart of a method according to an embodiment of the method for processing device data in the present application, and as shown in fig. 9, the attribute data of a new device may be received and stored, and the stored device data information may be continuously refined, so that the accuracy of device identification may also be improved.
Based on the method, the application provides a device data processing device. Fig. 10 is a block diagram of an embodiment of a device data processing apparatus according to the present application. As shown in fig. 10, the device data processing apparatus may include:
the data acquisition module 101 may be configured to acquire attribute data including parameter information of a specific application in the target device according to the stored configuration information;
the data processing module 102 may be configured to perform dimension reduction processing on the obtained attribute data, and obtain the attribute data after the dimension reduction processing;
the storage module 103 may be configured to store the attribute data after the dimension reduction processing based on a device to which the attribute data belongs.
The device data processing device can acquire the attribute data of the software information in the target device according to the preset acquisition requirement, stores the acquired attribute data after dimension reduction processing, and can provide data search support for device identification based on the device software information.
Fig. 11 is a schematic block diagram of another embodiment of a device data processing apparatus according to the present application. As shown in fig. 11, the device data processing apparatus may further include:
the weight value module 104 may be configured to set a weight value for the parameter information of the attribute data after the dimension reduction processing.
Of course, the attribute data including the set weight value may be stored when the storage module stores data. The weighted value of the parameter information can be further optimized and adjusted according to the characteristics of the collected data or the data processing requirements and the like. Therefore, the weight value module 104 according to this embodiment may include:
and the stability calculation module can be used for calculating a stable value of the attribute data and adjusting a weight value of parameter information in the attribute data according to a calculation result of the stable value.
Of course, a corresponding calculation mode may be set in the stability calculation module according to a requirement to calculate the value of the stability of the attribute data, and the weight value of the corresponding parameter information may be adjusted according to the calculated value of the stability of the attribute data. As one example, the stability calculation module may calculate the stable value of the attribute data by at least one of:
calculating the probability of converting the specified attribute data into another attribute data;
calculating the probability of converting the value of the designated attribute data into another value;
the probability that the specified attribute data derives another attribute data is calculated.
Fig. 12 is a schematic block diagram of another embodiment of a device data processing apparatus according to the present application. As shown in fig. 12, the device data processing apparatus may further include:
the acquisition rate calculating module 105 may be configured to calculate an acquisition rate of the attribute data, and update the configuration information according to a calculation result of the acquisition rate.
The collection strategy of the software information in the collection equipment can be effectively optimized by calculating the collection of the attribute data, the more reliable and efficient equipment software information is obtained, the effectiveness of the stored data is improved, and meanwhile, the accuracy of equipment identification can also be improved.
Of course, for a device that cannot match the identification, it may be regarded as a new device, and the data of the new device is stored. Fig. 13 is a schematic block diagram of another embodiment of a device data processing apparatus according to the present application. As shown in fig. 13, the device data processing apparatus may further include:
the new device processing module 106 may be configured to receive the attribute data identified as the new device, and send the attribute data of the new device to the storage module 103 for storage.
Based on the method, the application provides a device identification device. Fig. 14 is a schematic block diagram of an embodiment of an apparatus identification device according to the present application. As shown in fig. 14, the device identification apparatus may include:
the first data acquisition module 201 may be configured to acquire attribute data including parameter information of a specific application in a target device according to set configuration information;
the first data processing module 202 may be configured to compare the obtained attribute data with stored device attribute data, and search for stored device attribute data that matches the obtained attribute data;
the device identification module 203 may be configured to identify a device corresponding to the acquired attribute data according to the query result.
In another embodiment of the device identification apparatus, a device matching condition may be used in the first data processing module 202 to search for device attribute data matching the acquired attribute data. Therefore, in another embodiment of the device identification apparatus according to the present application, the first data processing module 202 may include:
and the matching module may be configured to set, as the device attribute data matched with the acquired attribute data, device attribute data that is the same as all the acquired attribute data of the target device or is the same as part of the acquired attribute data of the target device.
Fig. 15 is a schematic block diagram of an embodiment of a device identification module 203 in the device identification apparatus according to the present application. As shown in fig. 15, the device identification module 203 may include:
a matching setting unit 2031 operable to set a matching condition for identifying an apparatus based on the acquired attribute data and the stored apparatus attribute data;
an identifying unit 2032 may be configured to identify the device based on the set matching condition.
The present application may provide an embodiment of the matching condition of the recognition apparatus set in the matching setting unit 2031. Specifically, the matching condition set in the matching setting unit 2031 may include at least one of:
when the stored equipment attribute data matched with the acquired attribute data are found, taking the equipment corresponding to the equipment attribute data, the number of which is the same as the value of the acquired attribute data and meets the set first identification condition, as identified equipment;
when the stored equipment attribute data matched with the acquired attribute data is found, the equipment corresponding to the equipment attribute data, the equipment score of which is obtained by calculation according to the weight value of the set parameter information and meets the set second identification condition, of the equipment attribute data is used as the identified equipment;
when the stored device attribute data matched with the acquired attribute data is not found in the stored device attribute data, identifying the target device corresponding to the acquired attribute data as a new device;
when the same number of the stored device attribute data and the obtained attribute data does not meet a set first identification condition, identifying the target device corresponding to the obtained attribute data as a new device;
and identifying the target equipment corresponding to the acquired attribute data as new equipment when the equipment score of the equipment attribute data calculated according to the weight value of the set parameter information does not meet a set second identification condition.
The first identification condition and the second identification condition can be reasonably set according to identification requirements or attribute data characteristics. For example, the first recognition condition may be set such that the number of the attribute data having the same value is the largest, or the number of the attribute data having the same value is required to reach 99%, and the second recognition condition may be set such that a certain score threshold is reached. Specifically, reference may also be made to other embodiments in the present application, which are not described herein in detail.
Of course, the embodiment can be applied to business systems with various equipment identifications. The method and the device for identifying the equipment based on the software information in the equipment can effectively identify the equipment through the software information in the equipment under the condition that the identification of the hardware equipment information is difficult to realize under the control removing and hardware sensitive information prevention and control measures in the future. Therefore, the present application further provides an apparatus identification system, and in particular, the system of the present application may be configured to include:
the storage unit can be used for storing the acquired attribute data of the equipment, including the software information of the equipment;
the processing unit may be configured to acquire attribute data to be processed of a target device, where the attribute data includes the target device software information; the attribute data to be processed and the attribute data stored in the storage unit can be matched, and the target device is identified according to the matching result.
Through the embodiments, it can be clearly recognized that the application provides a device identification and data processing method, device and system, which can identify a device through collected software information in the device, and realize the identification of the device when the hardware information of the device cannot meet the identification requirement of the device.
Although the present application refers to the data processing descriptions of collecting webrtc information, canvas information based on html5 technology, data storage and query, principal component analysis, etc., the present application is not limited to the case of data processing, interaction, which must be fully standard or the mentioned methods. The above description of the embodiments of the present application is only an application of some embodiments of the present application, and the solutions of the embodiments of the present application can also be implemented by a processing method slightly modified based on some standards and methods. Of course, other non-inventive variations of the processing method steps described in the above embodiments consistent with the present application may still be implemented in the same application, and are not described herein again.
Although the present application provides method steps as described in an embodiment or flowchart, more or fewer steps may be included based on conventional or non-inventive means. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or client product executes, it may execute sequentially or in parallel (e.g., in the context of parallel processors or multi-threaded processing) according to the embodiments or methods shown in the figures.
The units or modules illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, in implementing the present application, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units.
Those skilled in the art will also appreciate that, in addition to implementing the controller as purely computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may therefore be considered as a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
From the above description of the embodiments, it is clear to those skilled in the art that the present application can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, or the like, and includes several instructions for enabling a computer device (which may be a personal computer, a mobile terminal, a server, or a network device) to execute the method according to the embodiments or some parts of the embodiments of the present application.
The embodiments in the present specification are described in a progressive manner, and the same or similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. The application is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
While the present application has been described with examples, those skilled in the art will appreciate that there are numerous variations and permutations of the present application without departing from the spirit of the application, and it is intended that the appended claims encompass such variations and modifications without departing from the spirit of the application.
Claims (16)
1. A method of device data processing, the method comprising:
acquiring attribute data including parameter information of a designated application in target equipment according to the set configuration information;
performing dimensionality reduction on the acquired attribute data to acquire the attribute data subjected to dimensionality reduction, wherein the parameter information of the attribute data subjected to dimensionality reduction is provided with a weighted value; storing the attribute data after the dimensionality reduction processing based on the equipment to which the attribute data belongs;
the stability of the attribute data is also calculated, the weight value of parameter information in the attribute data is adjusted according to the calculation result of the stability, and the stability represents the probability that the same attribute data of the same equipment changes under different acquisition times;
the calculating the stability of the attribute data comprises at least one of the following modes:
calculating the probability of converting the specified attribute data into another attribute data;
calculating the probability of converting the value of the designated attribute data into another value;
the probability that the specified attribute data derives another attribute data is calculated.
2. The device data processing method of claim 1, wherein the method further comprises
And calculating the acquisition rate of the attribute data, and updating the configuration information according to the calculation result of the acquisition rate.
3. A method for device data processing according to any of claims 1-2, wherein the method further comprises:
receiving attribute data identified as a new device, and storing the attribute data of the new device.
4. A method for device identification, the method comprising:
acquiring attribute data including parameter information of a designated application in target equipment according to set configuration information;
comparing the acquired attribute data with stored equipment attribute data, and searching the stored equipment attribute data matched with the acquired attribute data; the stored device attribute data includes: calculating the stability of attribute data of a target device acquired in advance, and adjusting the weight value of parameter information in the attribute data according to the calculation result of the stability to obtain the stability, wherein the stability represents the probability of the change of the same attribute data of the same device under different acquisition times;
identifying equipment corresponding to the acquired attribute data according to the query result;
the stability of the attribute data includes at least one of:
the probability that the specified attribute data is converted into another attribute data;
a probability that a value of the specified attribute data is converted into another value;
the specified attribute data derives a probability of another attribute data.
5. A device identification method as claimed in claim 4, wherein said finding stored device attribute data that matches said obtained attribute data comprises:
and searching all the acquired attribute data of the target equipment or equipment attribute data with the same part of attribute data in the stored equipment attribute data.
6. The device identification method according to claim 4, wherein the identifying the device corresponding to the acquired attribute data according to the query result comprises:
and when the stored equipment attribute data matched with the acquired attribute data is found, taking the equipment corresponding to the equipment attribute data which meets the requirements of the same number and the maximum number and/or the preset percentage of the values of the acquired attribute data as the equipment corresponding to the acquired attribute data.
7. The device identification method according to claim 4, wherein the identifying the device corresponding to the acquired attribute data according to the query result comprises:
when the stored equipment attribute data matched with the acquired attribute data is found, calculating an equipment score corresponding to the equipment attribute data according to the set weight value of the parameter information in the matched equipment attribute data; and taking the equipment corresponding to the equipment attribute data with the equipment score reaching the preset requirement as the equipment corresponding to the acquired attribute data.
8. A device identification method according to any of claims 4-7, characterized in that the method further comprises:
identifying the target device corresponding to the acquired attribute data as a new device when at least one of the following is satisfied:
the stored device attribute data matched with the acquired attribute data is not found in the stored device attribute data;
the stored device attribute data does not meet the requirement that the same number of values as the obtained attribute data is the most and/or reaches a predetermined percentage;
the device score of the stored device attribute data does not meet a predetermined requirement.
9. An apparatus for data processing of a device, the apparatus comprising:
the data acquisition module is used for acquiring attribute data of the target equipment including the parameter information of the designated application according to the stored configuration information;
the data processing module is used for carrying out dimensionality reduction on the acquired attribute data and acquiring the attribute data subjected to dimensionality reduction;
the storage module is used for storing the attribute data after the dimension reduction processing based on the equipment to which the attribute data belongs;
the weighted value module is used for setting weighted values for the parameter information of the attribute data after the dimension reduction processing;
the stability calculation module is used for calculating a stable value of the attribute data and adjusting a weight value of parameter information in the attribute data according to a calculation result of the stable value; the stability calculation module calculating the stable value of the attribute data comprises at least one of the following modes:
calculating the probability of converting the specified attribute data into another attribute data;
calculating the probability of converting the value of the designated attribute data into another value;
the probability that the specified attribute data derives another attribute data is calculated.
10. An apparatus data processing arrangement according to claim 9, characterized in that the arrangement further comprises:
and the acquisition rate calculation module is used for calculating the acquisition rate of the attribute data and updating the configuration information according to the calculation result of the acquisition rate.
11. An apparatus data processing arrangement according to claim 9, characterized in that the arrangement further comprises:
and the new equipment processing module is used for receiving the attribute data identified as the new equipment and sending the attribute data of the new equipment to the storage module for storage.
12. An apparatus for device identification, the apparatus comprising:
the first data acquisition module is used for acquiring attribute data of the target equipment including the parameter information of the designated application according to the set configuration information;
the first data processing module is used for comparing the acquired attribute data with stored equipment attribute data and searching the stored equipment attribute data matched with the acquired attribute data; the stored device attribute data includes: calculating the stability of attribute data of a target device acquired in advance, and adjusting the weight value of parameter information in the attribute data according to the calculation result of the stability to obtain the stability, wherein the stability represents the probability of the change of the same attribute data of the same device under different acquisition times;
the equipment identification module is used for identifying equipment corresponding to the acquired attribute data according to the query result;
the stability of the attribute data includes at least one of:
the probability that the specified attribute data is converted into another attribute data;
a probability that a value of the specified attribute data is converted into another value;
the specified attribute data derives a probability of another attribute data.
13. The device identification apparatus of claim 12, wherein the first data processing module comprises:
and the matching module is used for setting the device attribute data which is the same as all the acquired attribute data of the target device or the partial attribute data of the acquired target device as the device attribute data matched with the acquired attribute data.
14. The device identification apparatus of claim 12, wherein the device identification module comprises:
a matching setting unit configured to set a matching condition for identifying a device based on the acquired attribute data and the stored device attribute data;
and the identification unit is used for identifying the equipment based on the set matching condition.
15. A device recognition apparatus according to claim 14, wherein the matching condition set in the matching setting unit includes at least one of:
when the stored equipment attribute data matched with the acquired attribute data are found, taking the equipment corresponding to the equipment attribute data, the number of which is the same as the value of the acquired attribute data and meets the set first identification condition, as identified equipment;
when the stored equipment attribute data matched with the acquired attribute data is found, the equipment corresponding to the equipment attribute data, the equipment score of which is obtained by calculation according to the weight value of the set parameter information and meets the set second identification condition, of the equipment attribute data is used as the identified equipment;
when the stored device attribute data matched with the acquired attribute data is not found in the stored device attribute data, identifying the target device corresponding to the acquired attribute data as a new device;
when the same number of the stored device attribute data and the obtained attribute data does not meet a set first identification condition, identifying the target device corresponding to the obtained attribute data as a new device;
and identifying the target equipment corresponding to the acquired attribute data as new equipment when the equipment score of the equipment attribute data calculated according to the weight value of the set parameter information does not meet a set second identification condition.
16. A device identification system, the system configured to include:
a storage unit for storing the attribute data obtained by the method of any one of claims 1 to 3; the attribute data comprises attribute data for adjusting the weight value of the parameter information in the attribute data according to the calculation result of the stability of the attribute data;
the processing unit is used for acquiring attribute data to be processed of target equipment, including software information of the target equipment; and the attribute data to be processed is matched with the attribute data stored in the storage unit, and the target equipment is identified according to the matching result.
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| CN108241561A (en) * | 2017-12-25 | 2018-07-03 | 深圳回收宝科技有限公司 | A kind of generation method, server and the storage medium of terminal detection model |
| CN109782631B (en) * | 2019-03-08 | 2021-06-18 | 重庆邮电大学 | Intelligent household equipment identification method based on characteristic value comparison |
| CN109960922B (en) * | 2019-03-11 | 2021-09-07 | 北京三快在线科技有限公司 | Method and device for identifying newly activated equipment |
| CN110162959A (en) * | 2019-05-31 | 2019-08-23 | 北京顶象技术有限公司 | Data processing method and device based on device-fingerprint |
| CN110598472B (en) * | 2019-09-18 | 2022-03-22 | 广州虎牙科技有限公司 | Equipment identification method, device, server and storage medium |
| CN112000853A (en) * | 2020-07-31 | 2020-11-27 | 天翼电子商务有限公司 | Method, medium, client and server for generating/feeding back unique identifier of equipment |
| CN113271232B (en) * | 2020-10-27 | 2022-01-11 | 苏州铁头电子信息科技有限公司 | Online office network disturbance processing method and device |
| CN114510525B (en) * | 2022-04-18 | 2022-08-30 | 深圳丰尚智慧农牧科技有限公司 | Data format conversion method and device, computer equipment and storage medium |
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