CN116821888A - Equipment identification method and device, storage medium and electronic equipment - Google Patents
Equipment identification method and device, storage medium and electronic equipment Download PDFInfo
- Publication number
- CN116821888A CN116821888A CN202310595055.0A CN202310595055A CN116821888A CN 116821888 A CN116821888 A CN 116821888A CN 202310595055 A CN202310595055 A CN 202310595055A CN 116821888 A CN116821888 A CN 116821888A
- Authority
- CN
- China
- Prior art keywords
- identifier
- type
- target
- equipment
- identification
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 56
- 238000001514 detection method Methods 0.000 claims abstract description 130
- 238000012545 processing Methods 0.000 claims abstract description 70
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 69
- 238000011084 recovery Methods 0.000 claims description 13
- 238000012549 training Methods 0.000 claims description 11
- 238000004590 computer program Methods 0.000 claims description 6
- 238000002372 labelling Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 description 13
- 238000004891 communication Methods 0.000 description 8
- 230000006870 function Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 4
- 210000002569 neuron Anatomy 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000013527 convolutional neural network Methods 0.000 description 2
- 238000007477 logistic regression Methods 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000012913 prioritisation Methods 0.000 description 2
- 230000000306 recurrent effect Effects 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 238000012706 support-vector machine Methods 0.000 description 2
- 101150053844 APP1 gene Proteins 0.000 description 1
- 101100055496 Arabidopsis thaliana APP2 gene Proteins 0.000 description 1
- 101100189105 Homo sapiens PABPC4 gene Proteins 0.000 description 1
- 102100039424 Polyadenylate-binding protein 4 Human genes 0.000 description 1
- 101100016250 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) GYL1 gene Proteins 0.000 description 1
- 230000004913 activation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000003066 decision tree Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
- 230000005236 sound signal Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/44—Program or device authentication
Landscapes
- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Collating Specific Patterns (AREA)
Abstract
The embodiment of the application discloses a device identification method, a device, a storage medium and electronic equipment, wherein the method comprises the following steps: and carrying out at least one round of identifier detection processing on the device fingerprint information of the target device based on the reference priority corresponding to at least one reference identifier type to obtain an identifier detection result, determining a target identifier device identification algorithm aiming at the device fingerprint information based on the identifier detection result, and calling the target identifier device identification algorithm to carry out device identification processing on the device fingerprint information to obtain the device identifier aiming at the target device.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a device identification method, a device identification apparatus, a storage medium, and an electronic device.
Background
In the related art, device identification is often performed based on a device fingerprint, which refers to a device feature or unique device Identification (ID) that can be used to uniquely identify a device. At present, the client can collect identifiers of corresponding devices to generate device fingerprint information, the server judges whether the devices associated with the identifiers in the device fingerprint information are historical devices according to a corresponding device identification algorithm, if so, the client issues a historical device ID, otherwise, the server issues a new device ID.
Disclosure of Invention
The embodiment of the application provides a device identification method, a device, a storage medium and electronic equipment, wherein the technical scheme is as follows:
in a first aspect, an embodiment of the present application provides a device identification method, where the method includes:
acquiring device fingerprint information of target devices;
performing at least one round of identifier detection processing on the device fingerprint information based on the reference priority corresponding to at least one reference identifier type to obtain an identifier detection result, and determining a target identifier device identification algorithm for the device fingerprint information based on the identifier detection result;
and calling the target identifier equipment identification algorithm to carry out equipment identification processing on the equipment fingerprint information to obtain equipment identification aiming at the target equipment.
In a second aspect, an embodiment of the present application provides a device identification apparatus, including:
the information acquisition module is used for acquiring the device fingerprint information of the target device;
the service determining module is used for carrying out at least one round of identifier detection processing on the equipment fingerprint information based on the reference priority corresponding to at least one reference identifier type to obtain an identifier detection result, and determining a target identifier equipment identification algorithm aiming at the equipment fingerprint information based on the identifier detection result;
and the identification processing module is used for calling the identifier equipment identification algorithm to perform equipment identification processing on the equipment fingerprint information so as to obtain the equipment identification aiming at the target equipment.
In a third aspect, embodiments of the present application provide a computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the above-described method steps.
In a fourth aspect, an embodiment of the present application provides an electronic device, which may include: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the above-mentioned method steps.
The technical scheme provided by the embodiments of the application has the beneficial effects that at least:
in one or more embodiments of the present application, the service platform performs at least one round of identifier detection processing on the device fingerprint information of the target device based on the reference priority corresponding to each reference identifier type to obtain an identifier detection result, and based on the identifier detection result, can determine a target identifier device identification algorithm for the device fingerprint information, so as to perform device identification. The whole equipment identification process is compatible with identifier detection processing modes corresponding to various reference identifier types, has good compatibility for different equipment, can avoid being limited to a fixed identifier equipment identification mode, can consider the accuracy and stability of a system for equipment identification by combining the reference priority corresponding to the configured reference identifier type, and can reduce the equipment identification calculation power consumption by the configured reference priority.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a device identification method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of another embodiment of a device identification method according to an embodiment of the present application;
fig. 3 is a schematic architecture diagram of a device identification scenario provided in an embodiment of the present application;
FIG. 4 is a schematic view of a device identification scenario provided by an embodiment of the present application;
FIG. 5 is a flow chart of reference priority adjustment according to an embodiment of the present application;
FIG. 6 is a device identification apparatus provided in an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the description of the present application, it should be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In the description of the present application, it should be noted that, unless expressly specified and limited otherwise, "comprise" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art. Furthermore, in the description of the present application, unless otherwise indicated, "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.
In the related art, the device identification adopts a fixed identifier device identification algorithm, and only the fixed identifier device identification algorithm is used in the device identification, so that certain limitations exist, and the accuracy and the stability cannot be considered.
The present application will be described in detail with reference to specific examples.
In one embodiment, as shown in fig. 1, a device identification method is specifically proposed, which can be implemented in dependence on a computer program, and can be run on a device identification apparatus based on von neumann system. The computer program may be integrated in the application or may run as a stand-alone tool class application. The device identification means may be a service platform.
The service platform may be a separate server device, for example: rack-mounted, blade, tower-type or cabinet-type server equipment or hardware equipment with stronger computing capacity such as workstations, mainframe computers and the like is adopted; the server cluster may also be a server cluster formed by a plurality of servers, and each server in the server cluster may be formed in a symmetrical manner, wherein each server is functionally equivalent and functionally equivalent in a transaction link, and each server may independently provide services to the outside, and the independent provision of services may be understood as no assistance of another server is needed.
Specifically, the device identification method comprises the following steps:
s102: acquiring device fingerprint information of target devices;
device fingerprint information refers to a device characteristic or unique device Identification (ID) that can be used to uniquely identify a device. The generation manner of the device fingerprint information may be "device fingerprint information generated based on the device explicit identifier": the client gathers a fit of an explicit identifier of the target device, e.g., including one or more of an international mobile equipment identity (internationalmobile equipment identity, IMEI), an application developer identifier (Identifier for vendor, IDFV), an open anonymous device identifier (open anonymous device identifier, OADI), etc.; the generation mode of the device fingerprint information may be "device fingerprint information generated based on the device implicit identifier": the client collects the implicit identifier of the target device, including fitting of one or more of device hardware information (device model, total amount of hard disk, total amount of memory), system information (system name, system version, system start-up time, etc.), network information (client networking IP), region information (device language, region, time zone), etc.
In one or more embodiments of the present disclosure, the device fingerprint information may include at least one of an explicit identifier and an implicit identifier, based on actual application conditions;
the service platform may be configured with a server, and any target device associated with the service platform may be configured with a client. The client on the target device may report the device fingerprint information of the device to the server on the service platform. The service platform can acquire the device fingerprint information of the target device at the moment.
Further, the service platform may be associated with multiple target devices, that is, the service end on the service platform may establish communication connection with the client on one or more target devices, where the client may directly establish communication connection with the service end, or may establish communication connection with the service end through other devices. The server may provide various types of services, and the client may initiate a service request to the server. The service request may include a query request, an order request, a payment request, and the like. In order to determine the device identifier of the target device where the client is located, the server on the service platform needs to identify the target device where the client is located based on the device fingerprint information reported by the client, so as to determine the device identifier, which may also be referred to as a device ID, that is, a device identifier that may uniquely identify the device, where the server is issued by the client.
S104: performing at least one round of identifier detection processing on the device fingerprint information based on the reference priority corresponding to at least one reference identifier type to obtain an identifier detection result, and determining a target identifier device identification algorithm for the device fingerprint information based on the identifier detection result;
the reference identifier type may be a fit of one or more of an IMEI type, an IDFV type, an OADI type, a device hardware information type, a system information type, a network information type, etc. identifier types.
Different reference identifier types are associated with different identifier device identification algorithms, wherein the identifier device identification algorithms are pre-configured algorithms for matching the identifier based on the reference identifier types with the device identifier issued by the client by the server, and the identifier device identification algorithms can also be called device recovery algorithms.
In the specification, the service platform can integrate a plurality of identifier equipment identification algorithms to form a server-side-based recovery algorithm architecture so as to improve the overall accuracy and stability of the equipment fingerprint system. Meanwhile, combining the conditions of different identifier equipment identification algorithms such as calculation power consumption, recovery efficiency, processing stability, processing records and the like, configuring reference priorities for corresponding reference identifier types, wherein the reference priorities are used for indicating the sequence of the identifier detection processing currently performed by the service platform;
if the reference priority A corresponding to the reference identifier type A is higher than the reference priority B corresponding to the reference identifier type A, the service platform firstly carries out identifier detection processing corresponding to the reference identifier type A on the equipment fingerprint information to obtain an identifier detection result;
schematically, the service platform may determine, based on the reference priority corresponding to at least one reference identifier type, what kind of identifier detection processing is performed on the current round according to the reference identifier type, so that identifier detection processing is performed on the device fingerprint information to obtain an identifier detection result, where the identifier detection result may include a presence type and an absence type, if the identifier detection result is the presence type, determine a target identifier device identification algorithm for the device fingerprint information, and if the identifier detection result is the absence type, determine, based on the reference priority corresponding to the reference identifier type, what kind of identifier detection processing is performed on the next round according to the reference identifier type, so that identifier detection processing is performed on the device fingerprint information to obtain an identifier detection result, and so on, to determine the target identifier device identification algorithm for the device fingerprint information.
Optionally, the reference identifier types include at least one reference dominant identifier type and at least one reference invisible identifier type, a first reference priority of the reference dominant identifier type being higher than a second reference priority of the reference invisible identifier type. Furthermore, the dominant identifier recovery is taken as the main and the recessive identifier recovery is taken as the auxiliary, so that the accuracy and stability of the system can be greatly improved, and the calculation force investment of the recessive identifier recovery is reduced.
S106: and calling the target identifier equipment identification algorithm to carry out equipment identification processing on the equipment fingerprint information to obtain equipment identification aiming at the target equipment.
It can be understood that after determining the target identifier device identification algorithm for the device fingerprint information based on the identification detection result, the service platform performs algorithm scheduling, and schedules the device retrieving process of the target device to the target identifier device identification algorithm, so as to perform device identification processing based on the device fingerprint information, thereby obtaining the device identification for the target device. The device identification is typically a device identification previously determined or assigned by the service platform for the target device.
In one or more embodiments of the present disclosure, the service platform performs at least one round of identifier detection processing on device fingerprint information of the target device based on reference priorities corresponding to each reference identifier type to obtain an identifier detection result, and may determine a target identifier device identification algorithm for the device fingerprint information based on the identifier detection result, so as to perform device identification. The whole equipment identification process is compatible with identifier detection processing modes corresponding to various reference identifier types, has good compatibility for different equipment, can avoid being limited to a fixed identifier equipment identification mode, can consider the accuracy and stability of a system for equipment identification by combining the reference priority corresponding to the configured reference identifier type, and can reduce the equipment identification calculation power consumption by the configured reference priority.
Referring to fig. 2, fig. 2 is a flow chart illustrating another embodiment of a device identification method according to the present application. Specific:
s202: acquiring device fingerprint information of target devices;
schematically, as shown in fig. 3, fig. 3 shows an architecture diagram of a device identification scenario, in which the parties involved in the device identification may be application software, such as APP1, APP2 in fig. 3,
the service platform is maintained with a service end, the target equipment is maintained with a client end, the service end can be in communication connection with the client ends on one or more target equipment, the client end can be in communication connection with the service end directly, and the client end can be in communication connection with the service end through other equipment. The server side can provide various types of services, and the client side can initiate service requests in the service scene to the server side. The service request may include a query request, an order request, a payment request, etc. initiated based on the service party application software. The client may collect device information from the target device to generate device fingerprint information and report the device fingerprint information, and the client may also cache a device identifier (e.g., a device ID), which may not be carried by the device fingerprint information in some scenarios.
The service end on the service platform can maintain a device retrieving function, the service end can maintain a plurality of identifier device identification algorithms so as to facilitate device retrieving, namely, in order to determine the device identifier of the target device where the client is located, the service end can execute the device identification method of one or more embodiments of the present specification based on the device fingerprint information reported by the client, and the target device where the client is located is identified by determining the target identifier device identification algorithm through algorithm scheduling so as to determine the device identifier which is issued by the client by the service end, which can also be called as the device ID, and refers to the device identifier which can uniquely identify the device.
Further, under the condition that the equipment identification recovery failure is determined, the server side can generate a new equipment identification for the target equipment corresponding to the client side and send the client side, and store the equipment information and the corresponding equipment identification.
S204: determining a target detection identifier type based on a reference priority corresponding to at least one reference identifier type;
the target detection identifier type may be understood as the identifier type determined by the service platform to be currently subjected to the identifier detection process.
S206: performing identifier detection processing on the equipment fingerprint information aiming at the target detection identifier type to obtain a target identification detection result, and determining the detection result type of the target identification detection result;
based on the detection result type, acquiring an identifier equipment identification algorithm associated with the target detection identifier type;
s208: and if the detection result type is the identifier non-existence type, acquiring a next target detection identifier type of the next reference priority of the target detection identifier type, taking the next target detection identifier type as the target detection identifier type, and executing the identifier detection processing of the device fingerprint information aiming at the target detection identifier type to obtain a target identification detection result.
In a specific implementation scenario, it is assumed that the reference identifier type includes 4 types and reference priorities, respectively: dominant identifier type a > dominant identifier type B > recessive identifier group a type > recessive identifier group B type. As shown in fig. 4, fig. 4 is a schematic view of a scene of device identification, where a client of a target device collects and uploads device fingerprint information to a server on a service platform, and the service platform is based on a reference priority corresponding to a reference identifier type: the method comprises the steps of determining that the current target detection identifier type is 'dominant identifier A type', and carrying out identifier detection processing corresponding to 'dominant identifier A type' on device fingerprint information ', wherein' dominant identifier A type > dominant identifier B type > recessive identifier group A type > recessive identifier group B type: detecting whether the fingerprint information of the equipment contains a valid dominant identifier A or not to obtain an identifier detection result 1;
if the identification detection result 1 is yes, and the identifier exists in the type, determining a target identifier device identification algorithm aiming at the device fingerprint information: dominant identifier recovery algorithm a; if the identifier detection result 1 is no, and the identifier does not exist in the type at the moment, the service platform is based on the reference priority corresponding to the type of the reference identifier: the method comprises the steps of obtaining the next target detection identifier type 'implicit identifier group B type' of the next reference priority of the target detection identifier type, determining the current target detection identifier type as 'dominant identifier type B', and carrying out identifier detection processing corresponding to 'dominant identifier type B' on device fingerprint information: detecting whether the fingerprint information of the equipment contains a valid dominant identifier B to obtain an identifier detection result 2;
if the identification detection result 2 is yes, and the identifier exists in the type, determining a target identifier device identification algorithm aiming at the device fingerprint information: a dominant identifier retrieving algorithm B, in which the device retrieves (identifies) successfully; if the identifier detection result 2 is no, and the identifier does not exist in the type at the moment, the service platform is based on the reference priority corresponding to the type of the reference identifier: the method comprises the steps of obtaining a next target detection identifier type 'implicit identifier group A type' of the next reference priority of the target detection identifier type 'explicit identifier A type > explicit identifier B type > implicit identifier group A type > implicit identifier group B type', and carrying out identifier detection processing corresponding to 'implicit identifier group A type' on device fingerprint information: detecting whether the fingerprint information of the equipment contains a valid hidden identifier group A or not to obtain an identification detection result 3;
if the identification detection result 3 is yes, determining a target identifier device identification algorithm aiming at the device fingerprint information when the identifier exists in the type: a hidden identifier retrieving algorithm A; if the identifier detection result 3 is no, and the identifier does not exist in the type at the moment, the service platform is based on the reference priority corresponding to the type of the reference identifier: the method comprises the steps of carrying out identifier detection processing corresponding to the implicit identifier group B type on the fingerprint information of the device by the dominant identifier A type > the dominant identifier B type > the implicit identifier group A type > the implicit identifier group B type: detecting whether the fingerprint information of the equipment contains a valid hidden identifier group B or not to obtain an identification detection result 4;
......
s210: and if the detection result type is the identifier existence type, acquiring an identifier equipment identification algorithm associated with the target detection identifier type, and taking the identifier equipment identification algorithm as a target identifier equipment identification algorithm aiming at the equipment fingerprint information.
S212: and calling the target identifier equipment identification algorithm to carry out equipment identification processing on the equipment fingerprint information to obtain equipment identification aiming at the target equipment.
S214: if the next target detection identifier type of the next reference priority of the target detection identifier type does not exist, determining that the equipment recovery fails, and generating a reference equipment identifier for the target equipment.
If the equipment recovery fails, the service platform generates a new equipment identifier for the target equipment as a reference equipment identifier, and the new reference equipment identifier can be stored by the client side, wherein the new equipment identifier is optional and can be returned.
In one or more embodiments of the present disclosure, a architecture based on a multi-device recovery algorithm is implemented, which can be compatible with identifier detection processing modes corresponding to multiple reference identifier types, has good compatibility for different devices, can avoid being limited to a fixed identifier device identification mode, and can compromise the accuracy and stability of a system for device identification by combining a reference priority corresponding to a configured reference identifier type, and can reduce the consumption of computing power for device identification by the configured reference priority.
Referring to fig. 5, fig. 5 is a flow chart of reference priority adjustment according to the present application.
S302: acquiring task processing state information corresponding to a reference identifier equipment identification algorithm associated with at least one reference identifier type;
the task processing state information can be understood as representing the current task processing state of the service or service module where the reference identifier device identification algorithm is located, and the task processing state information can be fit of one or more information parameters such as task processing amount, average task processing time, task response duration, task response delay and the like.
S304: determining priority adjustment information corresponding to a reference identifier type based on the task processing state information and the reference priority corresponding to the reference identifier type;
it can be understood that the service platform can maintain reference identifier equipment identification algorithms associated with multiple reference identifier types, provide equipment identification services by using service modules corresponding to the reference identifier equipment identification algorithms, the number of clients generally associated by the service platform is large, and priorities of service modules corresponding to each reference identifier equipment identification algorithm are different, so that in the situations of large equipment identification request amount and more processing tasks, in order to ease performance bottleneck of equipment identification, processing efficiency is improved, algorithm scheduling can be performed by combining task processing state information corresponding to the reference identifier equipment identification algorithms and reference priorities corresponding to the reference identifier types, and dynamic load balancing is realized by adopting priorities corresponding to the adjustment reference identifier types under the condition of considering original reference priorities by generating priority adjustment information.
In a possible implementation manner, an identifier priority adjustment model may be trained in advance, the task processing state information and the reference priority corresponding to the reference identifier type are input into the identifier priority adjustment model, and priority adjustment information corresponding to the reference identifier type is output, where the identifier priority adjustment model is obtained by training a plurality of data training samples corresponding to known labeling priority adjustment information.
Specifically, a large number of data training samples are obtained from an actual application environment in advance, feature information is extracted, sample data are marked, priority adjustment information labels are marked on each data training sample, and an initial identifier priority adjustment model based on a machine learning model is created. The identifier prioritization model may be trained on the initial identifier prioritization model using a large amount of sample data.
Illustratively, the machine learning model includes, but is not limited to, one or more implementations of LR (Logistic Regression, logistic regression model), SVM (Support Vector Machine ), decision tree, naive bayes classifier, CNN (Convolutional Neural Network ), RNN (Recurrent Neural Networks, recurrent neural network), etc., training the initial identifier priority adjustment model based on the labeled sample data, resulting in a trained identifier priority adjustment model.
Illustratively, in this embodiment, an initial identifier priority adjustment model may be created by using an error back propagation algorithm, after feature information is extracted, the feature information is input into the initial identifier priority adjustment model in the form of a feature vector, a training process of the identifier priority adjustment model generally comprises two parts of forward propagation and backward propagation, in the forward propagation process, input sample data is correspondingly operated by a transfer function (also called an activation function or a conversion function) of extracting feature information from an input layer of the model through hidden layer neurons (also called nodes), the extracted feature information is transferred to an output layer, wherein each layer of neuron state affects the next layer of neuron state, an actual output value-priority adjustment information is calculated at the output layer, an error loss of a priority adjustment information label marked by the actual output value and an expected output value is calculated through a set loss function, the parameter comprises a weight value and a threshold value of each layer of the model is adjusted based on the error loss, and after training is completed, the identifier priority adjustment model is generated.
S306: and performing reference priority adjustment based on the priority adjustment information.
The priority adjustment information may be understood as a priority adjustment value indicating the type of reference identifier to be adjusted, and the type of reference identifier, according to which the priority of the corresponding type of reference identifier to be adjusted may be priority-adjusted.
In one or more embodiments of the present disclosure, a service platform may dynamically adjust a reference priority under a situation that a device identification request is large and a processing task is more, so as to effectively alleviate a performance bottleneck of device identification, improve processing efficiency, perform algorithm scheduling by combining task processing status information corresponding to a reference identifier device identification algorithm and a reference priority corresponding to a reference identifier type, generate priority adjustment information, and implement dynamic load balancing by adopting adjustment of a priority corresponding to the reference identifier type while considering an original reference priority.
The device identification apparatus provided in the embodiment of the present application will be described in detail with reference to fig. 6. It should be noted that, the device identifying apparatus shown in fig. 6 is used to execute the method of the embodiment shown in fig. 1 to 5, and for convenience of explanation, only the portion relevant to the embodiment of the present application is shown, and specific technical details are not disclosed, please refer to the embodiment shown in fig. 1 to 5 of the present application.
Referring to fig. 6, a schematic structural diagram of a device identification apparatus according to an embodiment of the application is shown. The device identification means 1 may be implemented as all or part of the user terminal by software, hardware or a combination of both. According to some embodiments, the device identification apparatus 1 comprises an information acquisition module 11, a service determination module 12 and an identification processing module 13, in particular for:
an information acquisition module 11, configured to acquire device fingerprint information of a target device;
a service determining module 12, configured to perform at least one round of identifier detection processing on the device fingerprint information based on a reference priority corresponding to at least one reference identifier type to obtain an identifier detection result, and determine a target identifier device identification algorithm for the device fingerprint information based on the identifier detection result;
and the identification processing module 13 is used for calling the identifier equipment identification algorithm to perform equipment identification processing on the equipment fingerprint information so as to obtain the equipment identification aiming at the target equipment.
Optionally, the service determining module 12 is configured to:
determining a target detection identifier type based on a reference priority corresponding to at least one reference identifier type;
performing identifier detection processing on the equipment fingerprint information aiming at the target detection identifier type to obtain a target identification detection result, and determining the detection result type of the target identification detection result;
and based on the detection result type, acquiring an identifier device identification algorithm associated with the target detection identifier type, and taking the identifier device identification algorithm as a target identifier device identification algorithm aiming at the device fingerprint information.
Optionally, the service determining module 12 is configured to:
if the detection result type is the identifier existence type, acquiring an identifier equipment identification algorithm associated with the target detection identifier type;
and if the detection result type is the identifier non-existence type, acquiring a next target detection identifier type of the next reference priority of the target detection identifier type, taking the next target detection identifier type as the target detection identifier type, and executing the identifier detection processing of the device fingerprint information aiming at the target detection identifier type to obtain a target identification detection result.
Optionally, the device 1 is further configured to:
if the next target detection identifier type of the next reference priority of the target detection identifier type does not exist, determining that the equipment recovery fails, and generating a reference equipment identifier for the target equipment.
Optionally, the reference identifier types include at least one reference dominant identifier type and at least one reference invisible identifier type, a first reference priority of the reference dominant identifier type being higher than a second reference priority of the reference invisible identifier type.
Optionally, the device 1 is further configured to:
acquiring task processing state information corresponding to a reference identifier equipment identification algorithm associated with at least one reference identifier type;
determining priority adjustment information corresponding to a reference identifier type based on the task processing state information and the reference priority corresponding to the reference identifier type;
and performing reference priority adjustment based on the priority adjustment information.
Optionally, the device 1 is further configured to:
inputting the task processing state information and the reference priority corresponding to the reference identifier type into an identifier priority adjustment model, and outputting priority adjustment information corresponding to the reference identifier type;
the identifier priority adjustment model is obtained by training a plurality of data training samples corresponding to known labeling priority adjustment information.
It should be noted that, in the device identifying apparatus provided in the above embodiment, only the division of the above functional modules is used for illustration when the device identifying method is executed, and in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the device identification apparatus and the device identification method embodiment provided in the foregoing embodiments belong to the same concept, which embody the detailed implementation process in the method embodiment, and are not repeated herein.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
The embodiment of the present application further provides a computer storage medium, where the computer storage medium may store a plurality of instructions, where the instructions are suitable for being loaded by a processor and executed by the processor to perform the device identification method according to the embodiment shown in fig. 1 to 5, and the specific execution process may refer to the specific description of the embodiment shown in fig. 1 to 5, which is not repeated herein.
The present application also provides a computer program product, where at least one instruction is stored, where the at least one instruction is loaded by the processor and executed by the processor, where the specific execution process may refer to the specific description of the embodiment shown in fig. 1 to 5, and details are not repeated herein.
Referring to fig. 7, a block diagram of an electronic device according to an embodiment of the present disclosure is provided. The electronic device in this specification may include one or more of the following: processor 110, memory 120, input device 130, output device 140, and bus 150. The processor 110, the memory 120, the input device 130, and the output device 140 may be connected by a bus 150.
Processor 110 may include one or more processing cores. The processor 110 connects various parts within the overall terminal using various interfaces and lines, performs various functions of the terminal 100 and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 120, and invoking data stored in the memory 120. Alternatively, the processor 110 may be implemented in at least one hardware form of digital signal processing (digital signal processing, DSP), field-programmable gate array (field-programmable gate array, FPGA), programmable logic array (programmable logic Array, PLA). The processor 110 may integrate one or a combination of several of a central processor (central processing unit, CPU), an image processor (graphics processing unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for being responsible for rendering and drawing of display content; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 110 and may be implemented solely by a single communication chip.
The memory 120 may include a random access memory (random Access Memory, RAM) or a read-only memory (ROM). Optionally, the memory 120 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 120 may be used to store instructions, programs, code, sets of codes, or sets of instructions.
The input device 130 is configured to receive input instructions or data, and the input device 130 includes, but is not limited to, a keyboard, a mouse, a camera, a microphone, or a touch device. The output device 140 is used to output instructions or data, and the output device 140 includes, but is not limited to, a display device, a speaker, and the like. In the embodiment of the present disclosure, the input device 130 may be a temperature sensor for acquiring an operation temperature of the terminal. The output device 140 may be a speaker for outputting audio signals.
In addition, those skilled in the art will appreciate that the configuration of the terminal illustrated in the above-described figures does not constitute a limitation of the terminal, and the terminal may include more or less components than illustrated, or may combine certain components, or may have a different arrangement of components. For example, the terminal further includes components such as a radio frequency circuit, an input unit, a sensor, an audio circuit, a wireless fidelity (wireless fidelity, WIFI) module, a power supply, a bluetooth module, and the like, which are not described herein again.
In the embodiment of the present specification, the execution subject of each step may be the service platform described above. Optionally, the execution subject of each step is an operating system of the service platform. The operating system may be an android system, an IOS system, or other operating systems, which embodiments of the present specification are not limited to.
In the electronic device of fig. 7, the processor 110 may be configured to invoke the program stored in the memory 120 and execute to implement the device identification method as described in the various method embodiments of the present specification.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, or the like.
The foregoing disclosure is illustrative of the present application and is not to be construed as limiting the scope of the application, which is defined by the appended claims.
Claims (10)
1. A method of device identification, the method comprising:
acquiring device fingerprint information of target devices;
performing at least one round of identifier detection processing on the device fingerprint information based on the reference priority corresponding to at least one reference identifier type to obtain an identifier detection result, and determining a target identifier device identification algorithm for the device fingerprint information based on the identifier detection result;
and calling the target identifier equipment identification algorithm to carry out equipment identification processing on the equipment fingerprint information to obtain equipment identification aiming at the target equipment.
2. The method according to claim 1, wherein said performing at least one round of identifier detection processing on the device fingerprint information based on the reference priority corresponding to the at least one reference identifier type to obtain an identification detection result, and determining a target identifier device identification algorithm for the device fingerprint information based on the identification detection result, includes:
determining a target detection identifier type based on a reference priority corresponding to at least one reference identifier type;
performing identifier detection processing on the equipment fingerprint information aiming at the target detection identifier type to obtain a target identification detection result, and determining the detection result type of the target identification detection result;
and based on the detection result type, acquiring an identifier device identification algorithm associated with the target detection identifier type, and taking the identifier device identification algorithm as a target identifier device identification algorithm aiming at the device fingerprint information.
3. The method according to claim 2, wherein the obtaining an identifier device identification algorithm associated with the target detection identifier type based on the detection result type comprises:
if the detection result type is the identifier existence type, acquiring an identifier equipment identification algorithm associated with the target detection identifier type;
and if the detection result type is the identifier non-existence type, acquiring a next target detection identifier type of the next reference priority of the target detection identifier type, taking the next target detection identifier type as the target detection identifier type, and executing the identifier detection processing of the device fingerprint information aiming at the target detection identifier type to obtain a target identification detection result.
4. A method according to claim 3, characterized in that the method further comprises:
if the next target detection identifier type of the next reference priority of the target detection identifier type does not exist, determining that the equipment recovery fails, and generating a reference equipment identifier for the target equipment.
5. The method of claim 1, wherein the reference identifier types include at least one reference dominant identifier type and at least one reference invisible identifier type, a first reference priority of the reference dominant identifier type being higher than a second reference priority of the reference invisible identifier type.
6. The method according to claim 1, wherein the method further comprises:
acquiring task processing state information corresponding to a reference identifier equipment identification algorithm associated with at least one reference identifier type;
determining priority adjustment information corresponding to a reference identifier type based on the task processing state information and the reference priority corresponding to the reference identifier type;
and performing reference priority adjustment based on the priority adjustment information.
7. The method of claim 6, wherein the determining priority adjustment information for the reference identifier type based on the task processing state information and the reference priority corresponding to the reference identifier type comprises:
inputting the task processing state information and the reference priority corresponding to the reference identifier type into an identifier priority adjustment model, and outputting priority adjustment information corresponding to the reference identifier type;
the identifier priority adjustment model is obtained by training a plurality of data training samples corresponding to known labeling priority adjustment information.
8. A device identification apparatus, the apparatus comprising:
the information acquisition module is used for acquiring the device fingerprint information of the target device;
the service determining module is used for carrying out at least one round of identifier detection processing on the equipment fingerprint information based on the reference priority corresponding to at least one reference identifier type to obtain an identifier detection result, and determining a target identifier equipment identification algorithm aiming at the equipment fingerprint information based on the identifier detection result;
and the identification processing module is used for calling the identifier equipment identification algorithm to perform equipment identification processing on the equipment fingerprint information so as to obtain the equipment identification aiming at the target equipment.
9. A computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the method steps of any one of claims 1 to 7.
10. An electronic device, comprising: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the method steps of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310595055.0A CN116821888A (en) | 2023-05-24 | 2023-05-24 | Equipment identification method and device, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310595055.0A CN116821888A (en) | 2023-05-24 | 2023-05-24 | Equipment identification method and device, storage medium and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116821888A true CN116821888A (en) | 2023-09-29 |
Family
ID=88115786
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310595055.0A Pending CN116821888A (en) | 2023-05-24 | 2023-05-24 | Equipment identification method and device, storage medium and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116821888A (en) |
-
2023
- 2023-05-24 CN CN202310595055.0A patent/CN116821888A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US7831734B2 (en) | Method and system for remote configuration of network devices | |
| CN108696381B (en) | Protocol configuration method and device | |
| CN112784989B (en) | Inference system, inference method, electronic device, and computer storage medium | |
| CN108449410A (en) | Information management method, system and relevant apparatus in a kind of cloud platform | |
| CN114024972B (en) | Long connection communication method, system, device, equipment and storage medium | |
| CN108062243B (en) | Execution plan generation method, task execution method and device | |
| RU2697648C2 (en) | Traffic classification system | |
| CN113300854B (en) | Edge node capability expansion method, system and expansion box | |
| CN113342503B (en) | Real-time progress feedback method, device, equipment and storage medium | |
| CN110650209A (en) | Method and device for realizing load balance | |
| CN109348434A (en) | A kind of sending method of scene information, sending device and terminal device | |
| CN112579319A (en) | Service calling method and device based on LRU Cache optimization | |
| CN111813529B (en) | Data processing method, device, electronic equipment and storage medium | |
| CN117633102A (en) | Block chain data integration method, device, computer equipment and storage medium | |
| CN111614726B (en) | Data forwarding method, cluster system and storage medium | |
| CN116821888A (en) | Equipment identification method and device, storage medium and electronic equipment | |
| Yang et al. | Method of Interaction between Blockchain and the World outside the Chain based on Oracle Machine | |
| CN115185543B (en) | Model deployment method, packing method, device, equipment and storage medium | |
| CN116560790A (en) | Parallel simulation data processing method and related equipment based on interest management | |
| CN111756836B (en) | Information sending method and device based on event management model | |
| CN114579054A (en) | Data processing method and device, electronic equipment and computer readable medium | |
| CN114048512A (en) | Method and device for processing sensitive data | |
| CN113553206A (en) | Data event execution method and device, electronic equipment and computer readable medium | |
| CN113326060A (en) | Service request processing method, device and system and service configuration method and device | |
| CN117176728B (en) | Industrial Internet of things dispatching method and dispatching system based on cloud edge cooperative technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication |