CN114363893B - Method and equipment for determining hotspot sharing password failure - Google Patents

Abstract

The application aims to provide a method and equipment for determining hotspot sharing password failure, wherein the method comprises the following steps: obtaining a connection result corresponding to the last connection event of the target hotspot; if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot; and inputting the hotspot behavior characteristic information into a hotspot failure model, and determining whether a first sharing password of the target hotspot used by the last connection event fails or not according to the output of the hotspot failure model. The application realizes an efficient hotspot sharing password failure prediction method, provides a practical and reliable technical scheme for meeting the requirement that users use WiFi more safely and efficiently, and greatly improves the user experience effect.

Description

Method and equipment for determining hotspot sharing password failure

Technical Field

The application relates to the field of communication, in particular to a technology for determining hotspot sharing password failure.

Background

With the development of the age, the mobile internet technology has become an indispensable part of people's daily life, and people are most commonly used in the environment of work, study, entertainment consumption, etc. in which a wide-spread wireless hotspot (WiFi) is popular. In order to meet the demands of users for safe and efficient use of networks, many apps have been developed that implement free WiFi based on user sharing. However, the existing free WiFi APP has the problems that the accuracy of the WiFi password is not high, the hot spot of the invalid password cannot be updated in time, the success rate of connecting WiFi is low, and the like.

Disclosure of Invention

The application aims to provide a method and equipment for determining hotspot sharing password failure.

According to one aspect of the present application, there is provided a method for determining hotspot sharing password failure, the method comprising:

obtaining a connection result corresponding to the last connection event of the target hotspot; if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot;

and inputting the hotspot behavior characteristic information into a hotspot failure model, and determining whether a first sharing password of the target hotspot used by the last connection event fails or not according to the output of the hotspot failure model.

According to one aspect of the present application, there is provided a network device for determining hotspot sharing password failure, the device comprising:

the one-to-one module is used for obtaining a connection result corresponding to the last connection event of the target hotspot; if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot;

and the second module is used for inputting the hotspot behavior characteristic information into a hotspot failure model, and determining whether the first sharing password of the target hotspot used by the last connection event fails or not according to the output of the hotspot failure model.

According to one aspect of the present application, there is provided an apparatus for determining hotspot sharing password failure, wherein the apparatus includes:

a processor; and

a memory arranged to store computer executable instructions that, when executed, cause the processor to:

obtaining a connection result corresponding to the last connection event of the target hotspot; if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot;

and inputting the hotspot behavior characteristic information into a hotspot failure model, and determining whether a first sharing password of the target hotspot used by the last connection event fails or not according to the output of the hotspot failure model.

According to one aspect of the application, there is provided a computer readable medium storing instructions that, when executed, cause a system to:

obtaining a connection result corresponding to the last connection event of the target hotspot; if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot;

and inputting the hotspot behavior characteristic information into a hotspot failure model, and determining whether a first sharing password of the target hotspot used by the last connection event fails or not according to the output of the hotspot failure model.

Compared with the prior art, the method and the device have the advantages that the connection result corresponding to the last connection event of the target hotspot is obtained; if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot; and inputting the hotspot behavior characteristic information into a hotspot failure model, and determining whether the first sharing password of the target hotspot used by the last connection event fails or not according to the output of the hotspot failure model, so that an efficient hotspot sharing password failure prediction method is realized, a practical and reliable technical scheme is provided for meeting the requirement that users use WiFi more safely and efficiently, and the user experience effect is greatly improved.

Drawings

Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the accompanying drawings in which:

FIG. 1 illustrates a flow chart of a method for determining hotspot sharing password failure in accordance with one embodiment of the present application;

FIG. 2 illustrates a network device architecture diagram for determining hotspot sharing password failure according to one embodiment of the present application;

FIG. 3 illustrates a schematic diagram of a thermal point failure model, according to one embodiment of the application;

FIG. 4 illustrates a flow chart of a method for determining hotspot sharing password failure in accordance with one embodiment of the present application;

FIG. 5 illustrates an exemplary system that may be used to implement various embodiments described in the present application.

The same or similar reference numbers in the drawings refer to the same or similar parts.

Detailed Description

The application is described in further detail below with reference to the accompanying drawings.

In one exemplary configuration of the application, the terminal, the device of the service network, and the trusted party each include one or more processors (e.g., central processing units (Central Processing Unit, CPU)), input/output interfaces, network interfaces, and memory.

The Memory may include non-volatile Memory in a computer readable medium, random access Memory (Random Access Memory, RAM) and/or non-volatile Memory, etc., such as Read Only Memory (ROM) or Flash Memory (Flash Memory). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase-Change Memory (PCM), programmable Random Access Memory (Programmable Random Access Memory, PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (Dynamic Random Access Memory, DRAM), other types of Random Access Memory (RAM), read-Only Memory (ROM), electrically erasable programmable read-Only Memory (EEPROM), flash Memory or other Memory technology, read-Only Memory (Compact Disc Read-Only Memory, CD-ROM), digital versatile disks (Digital Versatile Disc, DVD) or other optical storage, magnetic cassettes, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by the computing device.

The device includes, but is not limited to, a user device, a network device, or a device formed by integrating a user device and a network device through a network. The user equipment includes, but is not limited to, any mobile electronic product which can perform man-machine interaction with a user (for example, perform man-machine interaction through a touch pad), such as a smart phone, a tablet computer and the like, and the mobile electronic product can adopt any operating system, such as an Android operating system, an iOS operating system and the like. The network device includes an electronic device capable of automatically performing numerical calculation and information processing according to a preset or stored instruction, and the hardware includes, but is not limited to, a microprocessor, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a programmable logic device (Programmable Logic Device, PLD), a field programmable gate array (Field Programmable Gate Array, FPGA), a digital signal processor (Digital Signal Processor, DSP), an embedded device, and the like. The network device includes, but is not limited to, a computer, a network host, a single network server, a plurality of network server sets, or a cloud of servers; here, the Cloud is composed of a large number of computers or network servers based on Cloud Computing (Cloud Computing), which is a kind of distributed Computing, a virtual supercomputer composed of a group of loosely coupled computer sets. Including but not limited to the internet, wide area networks, metropolitan area networks, local area networks, VPN networks, wireless Ad Hoc networks (Ad Hoc networks), and the like. Preferably, the device may be a program running on the user device, the network device, or a device formed by integrating the user device and the network device, the touch terminal, or the network device and the touch terminal through a network.

Of course, those skilled in the art will appreciate that the above-described devices are merely examples, and that other devices now known or hereafter may be present as applicable to the present application, and are intended to be within the scope of the present application and are incorporated herein by reference.

In the description of the present application, the meaning of "a plurality" is two or more unless explicitly defined otherwise.

Fig. 1 shows a flowchart of a method for determining a hotspot sharing password failure according to an embodiment of the present application, the method including step S11 and step S12. In step S11, the network device obtains a connection result corresponding to the last connection event of the target hotspot; if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot; in step S12, the network device inputs the hotspot behavior feature information into a hotspot failure model, and determines whether the first shared password of the target hotspot used by the last connection event fails according to the output of the hotspot failure model.

In step S11, the network device obtains a connection result corresponding to the last connection event of the target hotspot; and if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot. In some embodiments, the target hotspot is a free WiFi hotspot. In some embodiments, each time the user equipment attempting to connect to the target hotspot sends a connection result corresponding to the current connection event to the network equipment, where the connection result may indicate that the current connection is successful or may indicate that the current connection is failed, and preferably, the user equipment sends the connection result to the network equipment through an application based on user sharing that is installed on the user equipment and implements free WiFi. In some embodiments, the user device uses the first shared secret code issued by the network device to the target hotspot of the user device to attempt to connect to the target hotspot, and the network device issues the updated first shared secret code to the user device each time after the first shared secret code is updated. In some embodiments, the user device may request from the network device to obtain the first shared secret of the target hotspot before each attempt to connect to the target hotspot. In some embodiments, the first shared secret code is the latest shared secret code of the target hotspot in the hotspot sharing library of the network device at the connection time corresponding to the last connection event, and because the connection time is earlier than or equal to the current time, the latest shared secret code of the target hotspot in the hotspot sharing library of the network device at the connection time may be the same as or different from the latest shared secret code of the target hotspot in the hotspot sharing library of the network device at the current time. In some embodiments, the network device obtains a connection result corresponding to a last connection event of the target hotspot according to a time sequence from the current time based on a connection result corresponding to a connection event of each attempt to connect the target hotspot sent by each user device, if the connection result indicates a connection failure, obtains hotspot behavior feature information corresponding to the target hotspot, where the hotspot behavior feature information is constructed according to collected historical connection behavior data and near-real-time connection behavior data of the target hotspot, and the historical connection behavior data and the near-real-time connection behavior data of the target hotspot may be sent to the network device by the user device attempting to connect the target hotspot, or may also be sent to the network device by a user device attempting to connect the target hotspot through an application based on user sharing installed on the user device to implement free WiFi, or may also be sent to the network device by a routing device corresponding to the target hotspot. In some embodiments, historical connection behavior data corresponding to the target hotspot may be updated at predetermined times (e.g., daily) and cached in a high-speed storage database for training and prediction of subsequent hotspot failure prediction models.

In step S12, the network device inputs the hotspot behavior feature information into a hotspot failure model, and determines whether the first shared password of the target hotspot used by the last connection event fails according to the output of the hotspot failure model. In some embodiments, a connection result corresponding to a last connection event of the target hotspot is obtained, if the connection result indicates that the connection fails, hotspot behavior feature information corresponding to the target hotspot is obtained, the hotspot behavior feature information is input into a trained hotspot failure model, and whether a first sharing password of the target hotspot used by the last connection event fails or not can be determined according to output of the hotspot failure model. In some embodiments, the connection result further includes a first sharing password of the target hotspot used by the last connection event, and the first sharing password can be obtained directly from the connection result. In some embodiments, the first shared secret of the target hotspot used by the last connection event needs to be acquired from the user equipment corresponding to the last connection event. In some embodiments, as shown in fig. 3, the hotspot failure model is a multi-layer neural network model constructed by a machine learning technology, and includes an input layer, an intermediate hidden layer and an output layer, and logic regression is used for two classification, where the input of the hotspot failure model is hotspot behavior feature information, the hotspot failure model may directly output a first shared secret code of a target hotspot used by a last connection event, or the hotspot failure model may output failure prediction information corresponding to the target hotspot, the failure prediction information may include various possible prediction results (failure or validity) of whether the first shared secret code of the target hotspot fails and prediction accuracy information corresponding to each possible prediction result, and then whether the first shared secret code of the target hotspot fails may be determined according to the failure prediction information, or the failure prediction result information may include at least one failure prediction result information and prediction confidence information corresponding to each failure prediction result information, and the failure prediction result information corresponding to each failure prediction result (failure or validity) of the first shared secret code of the target hotspot, and then whether the failure prediction result (failure or validity) of the target hotspot is determined according to the at least one failure prediction result information. In some embodiments, training samples are constructed for a large number of hotspots, sample tags are constructed (for example, whether each shared password corresponding to a certain hotspot is invalid or not is judged according to whether the latest shared password of the hotspot is successfully connected or not), and a required hotspot invalidation model is obtained after training is performed on batch sample data through a classification model. The scheme realizes an efficient hotspot sharing password failure prediction method, provides a practical and reliable technical scheme for meeting the requirement that users use WiFi more safely and efficiently, and greatly improves the user experience effect.

In some embodiments, the method further comprises: if the connection result indicates that the connection is successful, the network device judges whether the first shared password of the target hotspot used by the last connection event is a new shared password of the target hotspot; if yes, determining that the first sharing password is valid; otherwise, determining that the first sharing password is invalid. In some embodiments, a connection result corresponding to a last connection event of a target hotspot is obtained, if the connection result indicates that the connection is successful, whether a first sharing password of the target hotspot used by the last connection event is a latest sharing password of the target hotspot in a hotspot sharing library of the network device is judged, and if yes, the first sharing password is determined to be valid; otherwise, determining that the first shared password is invalid.

In some embodiments, the method further comprises: if the first shared password of the target hotspot used by the last connection event is a new shared password of the target hotspot, the network device determines that the historical shared password of the target hotspot is invalid. In some embodiments, if the first shared password of the target hotspot used by the last connection event is the latest shared password of the target hotspot in the hotspot sharing library of the network device, it may be determined that the first shared password is valid, and it may also be determined that one or more historical shared passwords of the target hotspot issued by the network device before fail.

In some embodiments, the hotspot behavior feature information includes hotspot historical behavior feature information and hotspot near-real-time behavior feature information. In some embodiments, the hotspot historical behavior feature information is constructed according to collected historical connection behavior data of the target hotspot, the hotspot near-real-time behavior feature information is constructed according to collected near-real-time connection behavior data of the target hotspot, the historical connection behavior is a connection behavior with a time interval between a behavior occurrence time and a current time being greater than or equal to a predetermined time interval threshold, and the near-real-time connection behavior is a connection behavior with a time interval between a behavior occurrence time and a current time being less than or equal to a predetermined time interval threshold. In some embodiments, the hotspot historical behavior feature information and the hotspot near-real-time behavior feature information include, but are not limited to, number of connections, number of connection successes, number of connection failures, connection success rate, number of connection devices, number of connection successes, number of connection failure devices, type of connection errors, and the like.

In some embodiments, the hotspot historical behavior feature information includes a plurality of dimensions and a hotspot historical behavior feature set corresponding to each dimension, and the hotspot near-real-time behavior feature information includes at least one connection failure event and error related information corresponding to each connection failure event. In some embodiments, the dimensions include, but are not limited to, a time dimension, a connection error type dimension (e.g., no error, weak signal, timeout, etc., connection error type), a city in which the connection is located, and the like. In some embodiments, the time dimension may be a time period dimension, e.g., each time dimension may be approximately 1 day, approximately 3 days, approximately 5 days, approximately 1 week, approximately 2 weeks, approximately 3 weeks, approximately 1 month, approximately 2 months, approximately 3 months, etc. In some embodiments, the time dimension may also be a time period dimension, e.g., each time dimension may be a 00-05 period, 06-11 period, 12-17 period, 18-23 period, etc. In some embodiments, each dimension corresponds to a set of hotspot historical behavior features, each of which includes one or more hotspot historical behavior features (e.g., number of connections successful, number of connections failed, number of connections successful, number of connection failed devices, type of connection error, etc.). In some embodiments, the at least one connection failure event includes a current connection failure event corresponding to the last connection event. In some embodiments, the error-related information corresponding to the connection failure event includes, but is not limited to, error cause information, error type information, error level information, error status information, error code information, and the like.

In some embodiments, the hotspot behavior feature information further includes first weight information corresponding to the hotspot historical behavior feature information and second weight information corresponding to the hotspot near-real-time behavior feature information, where the first weight information is smaller than the second weight information. In some embodiments, the hotspot historical behavior feature information corresponds to different weight information with the hotspot near-real-time behavior feature information, and the second weight information corresponding to the hotspot near-real-time behavior feature information closer to the current time is greater than the first weight information corresponding to the hotspot historical behavior feature information farther from the current time. In some embodiments, the weight information is used to characterize the magnitude of the impact of the hotspot historical behavior feature information or the hotspot near-real-time behavior feature information in the training phase and the prediction phase of the hotspot failure prediction model.

In some embodiments, the method further comprises step S13 (not shown). In step S13, the network device determines the first weight information and the second weight information, where the determining the first weight information and the second weight information includes at least one of: acquiring a sharing password updating frequency corresponding to the target hotspot, and determining the first weight information and the second weight information according to the sharing password updating frequency; and acquiring the connection frequency corresponding to the target hotspot, and determining the first weight information and the second weight information according to the connection frequency. In some embodiments, a shared password update frequency corresponding to the target hotspot may be obtained, and the first weight information and the second weight information may be determined according to the shared password update frequency. In some embodiments, a connection frequency corresponding to the target hotspot may also be obtained, and according to the connection frequency, the first weight information and the second weight information may be determined. In some embodiments, the update frequency of the shared password corresponding to the target hotspot can be determined according to the time information of each update corresponding to the latest shared password of the target hotspot in the hotspot sharing library of the network device, then the first weight information and the second weight information can be determined according to the update frequency of the shared password, the higher the update frequency of the shared password is, the larger the second weight information is, the smaller the first weight information is, the lower the update frequency of the shared password is, the smaller the second weight information is, and the larger the first weight information is. In some embodiments, the connection frequency may be an attempted connection frequency of the target hotspot, or may also be a connection success frequency of the target hotspot. In some embodiments, the first weight information and the second weight information may be determined according to a connection frequency, where the higher the connection frequency is, the larger the second weight information is, the smaller the first weight information is, and the lower the connection frequency is, the smaller the second weight information is, and the larger the first weight information is.

In some embodiments, the hotspot historical behavior feature information includes a plurality of dimensions, a hotspot historical behavior feature set corresponding to each dimension, and sub-weight information corresponding to each dimension. In some embodiments, the hotspot historical behavior feature information further includes sub-weight information corresponding to each dimension, different dimensions correspond to different sub-weight information, the sub-weight information is used for representing the influence degree of one or more hotspot historical behavior features included in the hotspot historical behavior feature set corresponding to the dimension corresponding to the sub-weight information in the hotspot historical behavior feature information, according to the sub-weight information corresponding to each dimension and the first weight information corresponding to the hotspot historical behavior feature information, the target weight information corresponding to each dimension can be determined, and the target weight information is used for representing the influence degree of one or more hotspot historical behavior features included in the hotspot historical behavior feature set corresponding to the dimension corresponding to the target weight information in the training stage and the prediction stage of the failure prediction model. In some embodiments, the target weight information corresponding to each dimension may be a product of the sub weight information corresponding to the dimension and the first weight information corresponding to the hotspot historical behavior feature information.

In some embodiments, the method further comprises step S14 (not shown) and step S15 (not shown). In step S14, the network device determines a sub-weight allocation rule according to the dimension division rule corresponding to the plurality of dimensions; in step S15, the network device determines, according to the sub-weight allocation rule, sub-weight information corresponding to each dimension. In some embodiments, the dimension partitioning rule is used to determine how to partition all of the hotspot historical behavior features into a plurality of dimensions, each dimension corresponding to a hotspot historical behavior feature set, each hotspot historical behavior feature set including one or more hotspot historical behavior features. In some embodiments, the dimension partitioning rules may be partitioned by time intervals from the current time, e.g., each time dimension may be the day, 1 day ago, 2 days ago, 3 days ago, 4 days ago, 5 days ago, or each time dimension may also be within approximately 1 week, within approximately 2 weeks, within approximately 3 weeks, within approximately 4 weeks, etc. In some embodiments, the dimension partitioning rules may also be time-divided by time period, e.g., each time dimension may be 00-05 time periods, 06-11 time periods, 12-17 time periods, 18-23 time periods, etc. In some embodiments, the dimension partitioning rules may also be partitioned by error type, e.g., each time dimension may be a connection error type that is error free, weak, timeout, etc. In some embodiments, the corresponding sub-weight allocation rule may be determined according to a dimension division rule, for example, if the dimension division rule is divided according to a time interval from the current time, the sub-weight allocation rule may be that sub-weight information allocated to a dimension shorter than the time interval from the current time is larger, for example, if the dimension division rule is divided according to a time period, the sub-weight allocation rule information may be that sub-weight information allocated to a dimension of a day period is larger than that of a night period, and for example, if the dimension division rule is divided according to an error type, the sub-weight allocation rule information may be that sub-weight information allocated to a dimension of an error type corresponding to an error level is larger.

In some embodiments, the dimension partitioning rule is partitioning by time interval from the current time; wherein, the step S14 includes: and the network equipment determines a sub-weight allocation rule according to the time interval of each dimension from the current time, wherein the sub-weight allocation rule is used for indicating that the sub-weight information allocated to the dimension with the shorter time interval from the current time is larger. In some embodiments, if the dimension partitioning rule is to partition at a time interval from the current time, the sub-weight allocation rule may be that the sub-weight information allocated for the dimension shorter than the time interval from the current time is larger, for example, the sub-weight information allocated for the time dimension of the day is larger than the sub-weight information allocated for the time dimension before 1 day is larger than the sub-weight information allocated for the time dimension before 2 days, or, for example, the sub-weight information allocated for the time dimension in the last 1 week is larger than the sub-weight information allocated for the time dimension in the last 2 weeks.

In some embodiments, the method further comprises: the network device builds the hotspot failure model according to the hotspot behavior characteristic information corresponding to each hotspot and the tag information corresponding to each hotspot, wherein the tag information corresponding to each hotspot is used for indicating whether each sharing password corresponding to the hotspot is invalid or not. In some embodiments, a training sample is constructed according to hotspot behavior feature information corresponding to each hotspot in a large number of hotspots and tag information corresponding to the hotspot, where the tag information corresponding to each hotspot refers to an actual result or a real result of whether each sharing password corresponding to the hotspot fails. In some embodiments, training samples are constructed for a large number of hot spots, sample labels are constructed, and the training is performed on batch sample data through a classification model, so that a required hot spot failure model is obtained after the training is finished.

In some embodiments, the method further comprises: and the network equipment determines the label information corresponding to each hot spot according to whether the hot spot is successfully connected by the new sharing password. In some embodiments, for each hotspot, whether each sharing password corresponding to the hotspot is invalid may be determined according to whether each hotspot is successfully connected with the latest sharing password corresponding to the hotspot in the hotspot sharing library of the network device, and if the hotspot is successfully connected with the latest sharing password corresponding to the hotspot in the hotspot sharing library of the network device, it may be determined that other historical sharing passwords corresponding to the hotspot except for the latest sharing password corresponding to the hotspot in the hotspot sharing library of the network device are invalid, so that tag information corresponding to the hotspot may be determined.

In some embodiments, the step S12 includes a step S121 (not shown) and a step S122 (not shown). In step S121, the network device inputs the hotspot behavior feature information into a hotspot failure model, so as to obtain failure prediction information corresponding to the first shared password output by the hotspot failure model; in step S122, the network device determines whether the first shared secret is invalid according to the invalidation prediction information. In some embodiments, the invalidation prediction information may include various prediction possible results (invalidation or validity) of whether the first shared password of the target hotspot used by the last connection event is invalidated and prediction accuracy information corresponding to each prediction possible result, and then, according to the invalidation prediction information, whether the first shared password of the target hotspot is invalidated may be determined.

In some embodiments, the failure prediction information includes at least one failure prediction result information and prediction confidence information corresponding to each prediction result information; wherein, the step S122 includes: the network equipment determines target failure prediction result information from the at least one failure prediction result information according to the prediction confidence information corresponding to each prediction result information; and determining whether the first shared password is invalid or not according to the target invalidation prediction result information. In some embodiments, the failure prediction result information is used to represent various prediction results (failure or valid) of whether the first shared password of the target hotspot is failed, and according to the prediction confidence information corresponding to each failure prediction result information, the target failure prediction result information may be determined from at least one failure prediction result information, and then whether the first shared password of the target hotspot is failed is determined according to the target failure prediction result information. In some embodiments, failure prediction result information, of which the corresponding prediction confidence information is greater than a predetermined confidence threshold, may be determined as target failure prediction result information, or failure prediction result information, of which the corresponding prediction confidence information is maximum, may also be determined as target failure prediction result information.

In some embodiments, the method further comprises: if the first sharing password fails, the network device updates a hotspot failure flag corresponding to the first sharing password of the target hotspot in a hotspot failure flag library, wherein the hotspot failure flag library comprises at least one sharing password corresponding to each hotspot in the plurality of hotspots and a hotspot failure flag corresponding to each sharing password. In some embodiments, a hotspot failure flag library maintains, for each hotspot in a hotspot sharing library of the network device, one or more versions of a shared password corresponding to the hotspot and a hotspot failure flag of each shared password, where the hotspot failure flag is used to identify whether the corresponding shared password is failed, for example, a hotspot failure flag "0" indicates that the corresponding shared password is failed, and a hotspot failure flag "1" indicates that the corresponding shared password is valid. In some embodiments, according to whether the first shared password of the target hotspot fails, updating a hotspot failure flag corresponding to the first shared password of the target hotspot in the hotspot failure flag library, and if the first shared password fails, updating the hotspot failure flag corresponding to the first shared password of the hotspot in the hotspot failure flag library to be "0". For example, the hotspot failure flag library is { hotspot a { 'V1: 0}, hotspot B } {' V1: 1}, where "V1" in hotspot a is the first shared password of hotspot a, and "V1" in hotspot B is the first shared password of hotspot B, which indicates that the first shared password V1 of hotspot a is invalid, and the first shared password V2 of hotspot B is valid, and if it is determined that the first shared password V2 of hotspot B is invalid according to the output of the hotspot failure model, the hotspot failure flag corresponding to the first shared password V2 of hotspot B is updated to "0", and the updated hotspot failure flag library is { hotspot a: { 'V1: 0, }, and hotspot B {' V1: 0 }.

In some embodiments, the method further comprises: if the historical sharing password of the target hotspot fails, the network equipment updates a hotspot failure flag corresponding to the historical sharing password in a hotspot failure flag library. In some embodiments, if it is determined that one or more history sharing passwords of a target hotspot previously issued by the network device fail, the hotspot failure flags corresponding to the one or more history sharing passwords of the hotspot in the hotspot failure flag library are updated to "0". For example, the hotspot failure flag library is { hotspot a { ' V1: ' 0, ' V2: ' 1}, hotspot B { ' V1: ' 1, ' V2: ' 1}, where "V1" in hotspot a is the history sharing password issued before hotspot a, "V2" in hotspot a is the latest sharing password of hotspot a, "V1" in hotspot B is the history sharing password issued before hotspot B, and "V2" in hotspot B is the latest sharing password of hotspot B, which indicates that the history sharing password V1 of hotspot a is invalid, the latest sharing password V2 is valid, and both the history sharing password V1 and the latest sharing password V2 of hotspot B are valid, and if the history sharing password of hotspot B is determined to be invalid according to the output of the hotspot failure model, the updated hotspot failure flag corresponding to the history sharing password V1 of hotspot B is updated to be "0", and the hotspot failure flag library is { hotspot a: { V1: ' 0, ' V2': ' V1 } ' V1 }.

Fig. 2 shows a block diagram of a network device for determining hotspot sharing password failure, which device comprises a one-to-one module 11 and a two-to-two module 12, according to one embodiment of the present application. A one-to-one module 11, configured to obtain a connection result corresponding to a last connection event of the target hotspot; if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot; and the second module 12 is configured to input the hotspot behavior feature information into a hotspot failure model, and determine whether the first shared password of the target hotspot used by the last connection event fails according to the output of the hotspot failure model.

A one-to-one module 11, configured to obtain a connection result corresponding to a last connection event of the target hotspot; and if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot. In some embodiments, the target hotspot is a free WiFi hotspot. In some embodiments, each time the user equipment attempting to connect to the target hotspot sends a connection result corresponding to the current connection event to the network equipment, where the connection result may indicate that the current connection is successful or may indicate that the current connection is failed, and preferably, the user equipment sends the connection result to the network equipment through an application based on user sharing that is installed on the user equipment and implements free WiFi. In some embodiments, the user device uses the first shared secret code issued by the network device to the target hotspot of the user device to attempt to connect to the target hotspot, and the network device issues the updated first shared secret code to the user device each time after the first shared secret code is updated. In some embodiments, the user device may request from the network device to obtain the first shared secret of the target hotspot before each attempt to connect to the target hotspot. In some embodiments, the first shared secret code is the latest shared secret code of the target hotspot in the hotspot sharing library of the network device at the connection time corresponding to the last connection event, and because the connection time is earlier than or equal to the current time, the latest shared secret code of the target hotspot in the hotspot sharing library of the network device at the connection time may be the same as or different from the latest shared secret code of the target hotspot in the hotspot sharing library of the network device at the current time. In some embodiments, the network device obtains a connection result corresponding to a last connection event of the target hotspot according to a time sequence from the current time based on a connection result corresponding to a connection event of each attempt to connect the target hotspot sent by each user device, if the connection result indicates a connection failure, obtains hotspot behavior feature information corresponding to the target hotspot, where the hotspot behavior feature information is constructed according to collected historical connection behavior data and near-real-time connection behavior data of the target hotspot, and the historical connection behavior data and the near-real-time connection behavior data of the target hotspot may be sent to the network device by the user device attempting to connect the target hotspot, or may also be sent to the network device by a user device attempting to connect the target hotspot through an application based on user sharing installed on the user device to implement free WiFi, or may also be sent to the network device by a routing device corresponding to the target hotspot. In some embodiments, historical connection behavior data corresponding to the target hotspot may be updated at predetermined times (e.g., daily) and cached in a high-speed storage database for training and prediction of subsequent hotspot failure prediction models.

And the second module 12 is configured to input the hotspot behavior feature information into a hotspot failure model, and determine whether the first shared password of the target hotspot used by the last connection event fails according to the output of the hotspot failure model. In some embodiments, a connection result corresponding to a last connection event of the target hotspot is obtained, if the connection result indicates that the connection fails, hotspot behavior feature information corresponding to the target hotspot is obtained, the hotspot behavior feature information is input into a trained hotspot failure model, and whether a first sharing password of the target hotspot used by the last connection event fails or not can be determined according to output of the hotspot failure model. In some embodiments, the connection result further includes a first sharing password of the target hotspot used by the last connection event, and the first sharing password can be obtained directly from the connection result. In some embodiments, the first shared secret of the target hotspot used by the last connection event needs to be acquired from the user equipment corresponding to the last connection event. In some embodiments, as shown in fig. 3, the hotspot failure model is a multi-layer neural network model constructed by a machine learning technology, and includes an input layer, an intermediate hidden layer and an output layer, and logic regression is used for two classification, where the input of the hotspot failure model is hotspot behavior feature information, the hotspot failure model may directly output a first shared secret code of a target hotspot used by a last connection event, or the hotspot failure model may output failure prediction information corresponding to the target hotspot, the failure prediction information may include various possible prediction results (failure or validity) of whether the first shared secret code of the target hotspot fails and prediction accuracy information corresponding to each possible prediction result, and then whether the first shared secret code of the target hotspot fails may be determined according to the failure prediction information, or the failure prediction result information may include at least one failure prediction result information and prediction confidence information corresponding to each failure prediction result information, and the failure prediction result information corresponding to each failure prediction result (failure or validity) of the first shared secret code of the target hotspot, and then whether the failure prediction result (failure or validity) of the target hotspot is determined according to the at least one failure prediction result information. In some embodiments, training samples are constructed for a large number of hotspots, sample tags are constructed (for example, whether each shared password corresponding to a certain hotspot is invalid or not is judged according to whether the latest shared password of the hotspot is successfully connected or not), and a required hotspot invalidation model is obtained after training is performed on batch sample data through a classification model. The scheme realizes an efficient hotspot sharing password failure prediction method, provides a practical and reliable technical scheme for meeting the requirement that users use WiFi more safely and efficiently, and greatly improves the user experience effect.

In some embodiments, the apparatus is further to: if the connection result indicates that the connection is successful, judging whether the first shared password of the target hotspot used by the last connection event is a new shared password of the target hotspot or not; if yes, determining that the first sharing password is valid; otherwise, determining that the first sharing password is invalid. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the apparatus is further to: and if the first shared password of the target hotspot used by the last connection event is a new shared password of the target hotspot, determining that the historical shared password of the target hotspot is invalid. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the hotspot behavior feature information includes hotspot historical behavior feature information and hotspot near-real-time behavior feature information. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the hotspot historical behavior feature information includes a plurality of dimensions and a hotspot historical behavior feature set corresponding to each dimension, and the hotspot near-real-time behavior feature information includes at least one connection failure event and error related information corresponding to each connection failure event. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the hotspot behavior feature information further includes first weight information corresponding to the hotspot historical behavior feature information and second weight information corresponding to the hotspot near-real-time behavior feature information, where the first weight information is smaller than the second weight information. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the apparatus further comprises a three module 13 (not shown). A third module 13, configured to determine the first weight information and the second weight information, where the determining the first weight information and the second weight information includes at least one of: acquiring a sharing password updating frequency corresponding to the target hotspot, and determining the first weight information and the second weight information according to the sharing password updating frequency; and acquiring the connection frequency corresponding to the target hotspot, and determining the first weight information and the second weight information according to the connection frequency. The implementation of a three-module 13 is the same as or similar to the embodiment related to step S13 in fig. 1, and thus is not described in detail herein, and is incorporated by reference.

In some embodiments, the hotspot historical behavior feature information includes a plurality of dimensions, a hotspot historical behavior feature set corresponding to each dimension, and sub-weight information corresponding to each dimension. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the apparatus further comprises a four module 14 (not shown) and a five module 15 (not shown). A four-module 14, configured to determine a sub-weight allocation rule according to the dimension division rule corresponding to the plurality of dimensions; and a five module 15, configured to determine the sub-weight information corresponding to each dimension according to the sub-weight allocation rule. The implementation manner of a four module 14 and a five module 15 is the same as or similar to the embodiment of steps S14 and S15 in fig. 1, and thus is not described in detail herein, and is incorporated by reference herein.

In some embodiments, the dimension partitioning rule is partitioning by time interval from the current time; wherein the four modules 14 are for: and determining a sub-weight allocation rule according to the time interval of each dimension from the current time, wherein the sub-weight allocation rule is used for indicating that the sub-weight information allocated to the dimension is larger when the time interval from the current time is shorter. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the apparatus is further to: and constructing the hotspot failure model according to the hotspot behavior characteristic information corresponding to each hotspot and the tag information corresponding to each hotspot, wherein the tag information corresponding to each hotspot is used for indicating whether each sharing password corresponding to the hotspot is invalid or not. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the apparatus is further to: and for each hotspot, determining the label information corresponding to the hotspot according to whether the hotspot is successfully connected by the new sharing password. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the two modules 12 include a two module 121 (not shown) and a two module 122 (not shown). A two-one module 121, configured to input the hotspot behavior feature information into a hotspot failure model, and obtain failure prediction information corresponding to the first shared password output by the hotspot failure model; and a second module 122, configured to determine whether the first shared secret is invalid according to the invalidation prediction information. The implementation of the two-one module 121 and the two-two module 122 is the same as or similar to the embodiment of steps S121 and S122 in fig. 1, and thus is not described in detail herein, and is incorporated by reference.

In some embodiments, the failure prediction information includes at least one failure prediction result information and prediction confidence information corresponding to each prediction result information; wherein, two module 122 are used for: determining target failure prediction result information from the at least one failure prediction result information according to the prediction confidence information corresponding to each prediction result information; and determining whether the first shared password is invalid or not according to the target invalidation prediction result information. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the apparatus is further to: and if the first shared password fails, updating a hotspot failure flag corresponding to the first shared password of the target hotspot in a hotspot failure flag library, wherein the hotspot failure flag library comprises at least one shared password corresponding to each hotspot in a plurality of hotspots and a hotspot failure flag corresponding to each shared password. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

In some embodiments, the apparatus is further to: and if the historical sharing password of the target hotspot fails, updating a hotspot failure mark corresponding to the historical sharing password in a hotspot failure mark library. The related operations are the same as or similar to those of the embodiment shown in fig. 1, and thus are not described in detail herein, and are incorporated by reference.

FIG. 4 illustrates a flow chart of a method for determining hotspot sharing password failure according to one embodiment of the present application.

As shown in fig. 4, obtaining hot spot information to be predicted, and judging whether the last connection of the hot spot to be predicted fails or not; if the connection is successful, judging whether the last connection uses the new sharing password of the hot spot, if so, updating a hot spot failure mark corresponding to the historical sharing password of the hot spot, and setting the hot spot failure mark corresponding to the historical sharing password of the hot spot as failure; if the connection fails, constructing a hotspot behavior feature corresponding to the hotspot, inputting the hotspot behavior feature into a trained hotspot failure prediction model, outputting whether the sharing password of the hotspot used by the last connection fails by the failure prediction model, if the sharing password fails, updating a hotspot failure flag corresponding to the sharing password of the hotspot, and setting the hotspot failure flag corresponding to the sharing password of the hotspot as failure.

FIG. 5 illustrates an exemplary system that can be used to implement various embodiments described in the present application.

In some embodiments, as shown in fig. 5, the system 300 can function as any of the devices of the various described embodiments. In some embodiments, system 300 may include one or more computer-readable media (e.g., system memory or NVM/storage 320) having instructions and one or more processors (e.g., processor(s) 305) coupled with the one or more computer-readable media and configured to execute the instructions to implement the modules to perform the actions described in the present application.

For one embodiment, the system control module 310 may include any suitable interface controller to provide any suitable interface to at least one of the processor(s) 305 and/or any suitable device or component in communication with the system control module 310.

The system control module 310 may include a memory controller module 330 to provide an interface to the system memory 315. Memory controller module 330 may be a hardware module, a software module, and/or a firmware module.

The system memory 315 may be used, for example, to load and store data and/or instructions for the system 300. For one embodiment, system memory 315 may include any suitable volatile memory, such as, for example, a suitable DRAM. In some embodiments, the system memory 315 may comprise a double data rate type four synchronous dynamic random access memory (DDR 4 SDRAM).

For one embodiment, system control module 310 may include one or more input/output (I/O) controllers to provide an interface to NVM/storage 320 and communication interface(s) 325.

For example, NVM/storage 320 may be used to store data and/or instructions. NVM/storage 320 may include any suitable nonvolatile memory (e.g., flash memory) and/or may include any suitable nonvolatile storage device(s) (e.g., one or more Hard Disk Drives (HDDs), one or more Compact Disc (CD) drives, and/or one or more Digital Versatile Disc (DVD) drives).

NVM/storage 320 may include storage resources that are physically part of the device on which system 300 is installed or which may be accessed by the device without being part of the device. For example, NVM/storage 320 may be accessed over a network via communication interface(s) 325.

Communication interface(s) 325 may provide an interface for system 300 to communicate over one or more networks and/or with any other suitable device. The system 300 may wirelessly communicate with one or more components of a wireless network in accordance with any of one or more wireless network standards and/or protocols.

For one embodiment, at least one of the processor(s) 305 may be packaged together with logic of one or more controllers (e.g., memory controller module 330) of the system control module 310. For one embodiment, at least one of the processor(s) 305 may be packaged together with logic of one or more controllers of the system control module 310 to form a System In Package (SiP). For one embodiment, at least one of the processor(s) 305 may be integrated on the same die as logic of one or more controllers of the system control module 310. For one embodiment, at least one of the processor(s) 305 may be integrated on the same die with logic of one or more controllers of the system control module 310 to form a system on chip (SoC).

In various embodiments, the system 300 may be, but is not limited to being: a server, workstation, desktop computing device, or mobile computing device (e.g., laptop computing device, handheld computing device, tablet, netbook, etc.). In various embodiments, system 300 may have more or fewer components and/or different architectures. For example, in some embodiments, system 300 includes one or more cameras, keyboards, liquid Crystal Display (LCD) screens (including touch screen displays), non-volatile memory ports, multiple antennas, graphics chips, application Specific Integrated Circuits (ASICs), and speakers.

The application also provides a computer readable storage medium storing computer code which, when executed, performs a method as claimed in any preceding claim.

The application also provides a computer program product which, when executed by a computer device, performs a method as claimed in any preceding claim.

The present application also provides a computer device comprising:

one or more processors;

a memory for storing one or more computer programs;

The one or more computer programs, when executed by the one or more processors, cause the one or more processors to implement the method of any preceding claim.

It should be noted that the present application may be implemented in software and/or a combination of software and hardware, e.g., using Application Specific Integrated Circuits (ASIC), a general purpose computer or any other similar hardware device. In one embodiment, the software program of the present application may be executed by a processor to perform the steps or functions described above. Likewise, the software programs of the present application (including associated data structures) may be stored on a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. In addition, some steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.

Furthermore, portions of the present application may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or techniques in accordance with the present application by way of operation of the computer. Those skilled in the art will appreciate that the form of computer program instructions present in a computer readable medium includes, but is not limited to, source files, executable files, installation package files, etc., and accordingly, the manner in which the computer program instructions are executed by a computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Herein, a computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by a computer.

Communication media includes media whereby a communication signal containing, for example, computer readable instructions, data structures, program modules, or other data, is transferred from one system to another. Communication media may include conductive transmission media such as electrical cables and wires (e.g., optical fibers, coaxial, etc.) and wireless (non-conductive transmission) media capable of transmitting energy waves, such as acoustic, electromagnetic, RF, microwave, and infrared. Computer readable instructions, data structures, program modules, or other data may be embodied as a modulated data signal, for example, in a wireless medium, such as a carrier wave or similar mechanism, such as that embodied as part of spread spectrum technology. The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. The modulation may be analog, digital or hybrid modulation techniques.

By way of example, and not limitation, computer-readable storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. For example, computer-readable storage media include, but are not limited to, volatile memory, such as random access memory (RAM, DRAM, SRAM); and nonvolatile memory such as flash memory, various read only memory (ROM, PROM, EPROM, EEPROM), magnetic and ferromagnetic/ferroelectric memory (MRAM, feRAM); and magnetic and optical storage devices (hard disk, tape, CD, DVD); or other now known media or later developed computer-readable information/data that can be stored for use by a computer system.

An embodiment according to the application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to operate a method and/or a solution according to the embodiments of the application as described above.

It will be evident to those skilled in the art that the application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the apparatus claims can also be implemented by means of one unit or means in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.

Claims (18)

1. A method for determining a hotspot sharing password failure, wherein the method comprises:

obtaining a connection result corresponding to the last connection event of the target hotspot; if the connection result indicates connection failure, acquiring hotspot behavior characteristic information corresponding to the target hotspot, wherein the hotspot behavior characteristic information is constructed according to collected historical connection behavior data and near-real-time connection behavior data of the target hotspot, the historical connection behavior is a connection behavior with a time interval of a behavior occurrence time from the current time being greater than or equal to a preset time interval threshold, and the near-real-time connection behavior is a connection behavior with a time interval of a behavior occurrence time from the current time being less than or equal to a preset time interval threshold;

and inputting the hotspot behavior characteristic information into a hotspot failure model, and determining whether a first sharing password of the target hotspot used by the last connection event fails according to the output of the hotspot failure model, wherein the hotspot failure model is constructed according to the hotspot behavior characteristic information corresponding to each hotspot in a plurality of hotspots and the tag information corresponding to each hotspot, and the tag information corresponding to each hotspot is used for indicating whether each sharing password corresponding to the hotspot fails.

2. The method of claim 1, wherein the method further comprises:

if the connection result indicates that the connection is successful, judging whether the first shared password of the target hotspot used by the last connection event is a new shared password of the target hotspot or not; if yes, determining that the first sharing password is valid; otherwise, determining that the first sharing password is invalid.

3. The method of claim 2, wherein the method further comprises:

and if the first shared password of the target hotspot used by the last connection event is a new shared password of the target hotspot, determining that the historical shared password of the target hotspot is invalid.

4. The method of claim 1, wherein the hotspot behavior feature information comprises hotspot historical behavior feature information and hotspot near-real-time behavior feature information.

5. The method of claim 4, wherein the hotspot historical behavior feature information comprises a plurality of dimensions and a hotspot historical behavior feature set corresponding to each dimension, and the hotspot near-real-time behavior feature information comprises at least one connection failure event and error-related information corresponding to each connection failure event.

6. The method of claim 4 or 5, wherein the hotspot behavior feature information further comprises first weight information corresponding to the hotspot historical behavior feature information and second weight information corresponding to the hotspot near-real-time behavior feature information, wherein the first weight information is smaller than the second weight information.

7. The method of claim 6, wherein the method further comprises:

determining the first weight information and the second weight information;

wherein the determining the first weight information and the second weight information includes at least one of:

acquiring a sharing password updating frequency corresponding to the target hotspot, and determining the first weight information and the second weight information according to the sharing password updating frequency;

and acquiring the connection frequency corresponding to the target hotspot, and determining the first weight information and the second weight information according to the connection frequency.

8. The method of claim 6 or 7, wherein the hotspot historical behavior feature information comprises a plurality of dimensions, a hotspot historical behavior feature set corresponding to each dimension, and sub-weight information corresponding to each dimension.

9. The method of claim 8, wherein the method further comprises:

determining a sub-weight distribution rule according to the dimension division rule corresponding to the plurality of dimensions;

and determining the sub-weight information corresponding to each dimension according to the sub-weight distribution rule.

10. The method of claim 9, wherein the dimension partitioning rule is partitioning by time interval from a current time;

wherein determining the sub-weight allocation rule according to the dimension division rule corresponding to the plurality of dimensions includes:

and determining a sub-weight allocation rule according to the time interval of each dimension from the current time, wherein the sub-weight allocation rule is used for indicating that the sub-weight information allocated to the dimension is larger when the time interval from the current time is shorter.

11. The method of claim 1, wherein the method further comprises:

and constructing the hotspot failure model according to the hotspot behavior characteristic information corresponding to each hotspot and the tag information corresponding to each hotspot, wherein the tag information corresponding to each hotspot is used for indicating whether each sharing password corresponding to the hotspot is invalid or not.

12. The method of claim 11, wherein the method further comprises:

and for each hotspot, determining the label information corresponding to the hotspot according to whether the hotspot is successfully connected by the new sharing password.

13. The method of claim 1, wherein the inputting the hotspot behavior feature information into a hotspot failure model, and determining whether the first shared password of the target hotspot used by the last connection event fails according to an output of the hotspot failure model, comprises:

inputting the hotspot behavior characteristic information into a hotspot failure model to obtain failure prediction information corresponding to the first shared password output by the hotspot failure model;

and determining whether the first shared password is invalid or not according to the invalidation prediction information.

14. The method of claim 13, wherein the failure prediction information includes at least one failure prediction result information and prediction confidence information corresponding to each prediction result information;

wherein the determining whether the first shared password is invalid according to the invalidation prediction information comprises:

determining target failure prediction result information from the at least one failure prediction result information according to the prediction confidence information corresponding to each prediction result information;

And determining whether the first shared password is invalid or not according to the target invalidation prediction result information.

15. The method of claim 1, wherein the method further comprises:

and if the first shared password fails, updating a hotspot failure flag corresponding to the first shared password of the target hotspot in a hotspot failure flag library, wherein the hotspot failure flag library comprises at least one shared password corresponding to each hotspot in a plurality of hotspots and a hotspot failure flag corresponding to each shared password.

16. The method of claim 15, wherein the method further comprises:

and if the historical sharing password of the target hotspot fails, updating a hotspot failure mark corresponding to the historical sharing password in a hotspot failure mark library.

17. An apparatus for determining a hotspot sharing password failure, the apparatus comprising:

a processor; and

a memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method of any one of claims 1 to 16.

18. A computer readable medium storing instructions that, when executed, cause a system to perform the operations of the method of any one of claims 1 to 16.