CN116709339A

CN116709339A - Detection method of application notification message and electronic equipment

Info

Publication number: CN116709339A
Application number: CN202211227605.5A
Authority: CN
Inventors: 司帅杰; 李展; 赵明明
Original assignee: Honor Device Co Ltd
Current assignee: Honor Device Co Ltd
Priority date: 2022-10-09
Filing date: 2022-10-09
Publication date: 2023-09-05

Abstract

The application provides a detection method of application notification messages and electronic equipment, which relate to the technical field of terminals and can remind risks to users and protect privacy and property safety of the users, wherein the method comprises the following steps: the electronic equipment receives a first notification message of a first application and acquires attribute information of the first notification message; the electronic equipment takes attribute information of the first notification message as input, and operates a text classification model to obtain a text classification prediction result; if the text classification prediction result indicates that the first notification message is a target notification message, the electronic equipment displays a second notification message; the second notification message comprises a notification title, notification content and risk prompt information created by the electronic device based on the first notification message, wherein the risk prompt information is used for prompting a user that the first notification message has risks.

Description

Detection method of application notification message and electronic equipment

Technical Field

The present application relates to the field of terminal technologies, and in particular, to a method for detecting an application notification message and an electronic device.

Background

With the continuous development of intelligent electronic devices (such as mobile phones) and the increase of the number of applications, the number of applications installed in the electronic devices is increasing. Various application programs often push notification messages to users in order to achieve different business purposes; wherein the content of the notification message pushed to the user by different application programs is different. For example, a news class application may push real-time news and hotspots to users; the investment financing class application may push an investment financing message to the user, etc.

However, some malicious applications have problems of revealing user privacy and affecting user property security with respect to the content of notification messages pushed to users.

Disclosure of Invention

The embodiment of the application provides a detection method of an application notification message and electronic equipment, which can remind a user of risks and protect privacy and property safety of the user.

The embodiment of the application adopts the following technical scheme:

in a first aspect, a method for detecting an application notification message is provided, and the method is applied to an electronic device, in which a first application is installed, and includes: the electronic equipment receives a first notification message of a first application and acquires attribute information of the first notification message; wherein the attribute information of the first notification message includes a notification title and notification content of the first notification message; the electronic equipment takes attribute information of the first notification message as input, and operates a text classification model to obtain a text classification prediction result; the text classification prediction result is used for indicating whether the first notification message is a target notification message, wherein the target notification message is a notification message with risk of revealing user privacy or losing user property; if the text classification prediction result indicates that the first notification message is a target notification message, the electronic equipment displays a second notification message; the second notification message comprises a notification title, notification content and risk prompt information created by the electronic device based on the first notification message, wherein the risk prompt information is used for prompting a user that the first notification message has risks.

Based on the first aspect, after the electronic equipment receives a first notification message of a first application, the electronic equipment acquires attribute information of the first notification message, and runs a text classification model by taking the attribute information of the first notification message as input so as to obtain a text classification prediction result; if the text classification prediction result indicates that the first notification message is the target notification message, the electronic equipment displays a second notification message, wherein the second notification message not only comprises a notification title and notification content of the first notification message, but also comprises risk prompt information created by the electronic equipment based on the first notification message.

In one implementation manner of the first aspect, the method further includes: the electronic equipment receives a first operation of a user on the second notification message; the first operation is used for triggering the electronic equipment to display a detail page of the notification content corresponding to the first notification message; the electronic device does not respond to the first operation; or, the electronic device displays a first interface in response to the first operation, the first interface not including a detail page of notification content of the first notification message.

In this implementation, the electronic device may be configured to not respond to the user's operation on the second notification message; or, the electronic device does not display the detail page of the notification content of the first notification message in response to the user's operation on the second notification message. Thus, the user cannot see the detail page of the notification content corresponding to the first notification message, and the problems of revealing the user privacy and property safety are avoided.

In one implementation manner of the first aspect, the method further includes: if the text classification prediction result indicates that the first notification message is the target notification message, the electronic device closes the message pushing service of the first application.

In this implementation, if the electronic device identifies that the first notification message is a target notification message, that is, the text classification prediction result indicates that the first notification message is a target notification message, the electronic device closes the message push service of the first application. Therefore, the first application can not push the notification message in the using process, and the problems of revealing the privacy and property safety of the user are fundamentally solved.

In an implementation manner of the first aspect, the electronic device stores a preset application list, where the preset application list includes application package names of applications whose user usage frequency is less than a preset frequency; the method further comprises the steps of: if the text classification prediction result indicates that the first notification message is a target notification message, the electronic equipment acquires an application package name of the first application; and if the application package name of the first application is in the preset list, the electronic equipment uninstalls the first application.

In this implementation manner, by matching the application package name of the first application with the preset list, if the application package name of the first application is in the preset list, the electronic device uninstalls the first application, that is, the electronic device uninstalls the application that is not commonly used by the user. Thus, the problems of revealing user privacy and property safety can be further avoided.

In an implementation manner of the first aspect, obtaining attribute information of the first notification message includes: if the first application is not the application downloaded by the electronic equipment from the application store, the electronic equipment acquires the attribute information of the first notification message.

Typically, before an application store of an electronic device (such as a mobile phone) is put on shelf, the application is detected, such as virus searching and killing, trojan searching and killing, and the like. If the potential safety hazard of the application is detected, the application is not put on shelf in the application store. That is, applications that can be put on shelf in the application store are not hidden by security, i.e., normal applications. In the subsequent use process, the target notification message is not pushed

In the implementation manner, by judging whether the first application is downloaded from the application store, if the first application is downloaded from the application store, the electronic device can normally display the first notification message pushed by the first application without executing the method of the application; if the first application is not downloaded from the application store, the electronic device executes the method of the application to identify whether the first notification message is a target notification message so as to reduce the power consumption of the device.

In an implementation manner of the first aspect, the electronic device stores a correspondence between the notification message and the risk prompt information; if the text classification prediction result indicates that the first notification message is a target notification message, the electronic device displays a second notification message, including: if the text classification prediction result indicates that the first notification message is a target notification message, the electronic equipment acquires attribute information of risk prompt information corresponding to the first notification message; the attribute information of the risk prompt information comprises a prompt box and prompt contents; the electronic device displays a second notification message based on the prompt box and the prompt content of the risk prompt message, and the notification title and the notification content of the first notification message.

In one implementation manner of the first aspect, the method further includes: the electronic equipment stores the first notification message and a text classification prediction result corresponding to the first notification message as a group of log files; if the number of the log files stored by the electronic equipment is larger than a preset number threshold, the electronic equipment sends a first notification message and a text classification prediction result corresponding to the first notification message to the server; the text classification prediction result corresponding to the first notification message is used for updating the text classification model; the electronic equipment receives the updated text classification model from the server; the updated text classification model is updated by the server through an over-the-air technology OTA.

In the implementation manner, the electronic device stores the first notification message and a text classification prediction result corresponding to the first notification message as a group of log files; if the number of the log files stored by the electronic equipment is larger than a preset number threshold, the electronic equipment sends a first notification message and a text classification prediction result corresponding to the first notification message to the server; based on the first notification message and the text classification prediction result corresponding to the first notification message, the server updates the text classification model through the over-the-air technology OTA, namely, when the server updates the system of the electronic equipment, the server updates the text classification model simultaneously, and the text classification model does not need to be updated independently, so that the resource utilization rate is improved.

In an implementation manner of the first aspect, after the electronic device acquires attribute information of the first notification message, the method further includes: the electronic equipment combines the notification title and the notification content, and performs text vectorization processing on the combined notification title and notification content to obtain a numerical vector with a preset length; the electronic device takes attribute information of a first notification message as input, operates a text classification model to obtain a text classification prediction result, and comprises: the electronic equipment takes the numerical vector with the preset length as input, operates a text classification model, and carries out vector quantity product calculation on the numerical vector with the preset length to obtain a text classification prediction result; if the vector quantity product is larger than the preset vector quantity product, the text classification prediction result indicates that the first notification message is a target notification message; wherein the value of the vector quantity product is used to characterize the frequency with which the target word appears in the first notification message.

In a second aspect, an electronic device is provided, which has the functions of implementing the first or second aspect. The functions can be realized by hardware, and can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the functions described above.

In a third aspect, an electronic device is provided that includes a display screen, a memory, and one or more processors; the display screen, the memory and the processor are coupled; the memory is for storing computer program code, the computer program code comprising computer instructions; the computer instructions, when executed by the processor, cause the electronic device to perform the steps of: the electronic equipment receives a first notification message of a first application and acquires attribute information of the first notification message; wherein the attribute information of the first notification message includes a notification title and notification content of the first notification message; the electronic equipment takes attribute information of the first notification message as input, and operates a text classification model to obtain a text classification prediction result; the text classification prediction result is used for indicating whether the first notification message is a target notification message, wherein the target notification message is a notification message with risk of revealing user privacy or losing user property; if the text classification prediction result indicates that the first notification message is a target notification message, the electronic equipment displays a second notification message; the second notification message comprises a notification title, notification content and risk prompt information created by the electronic device based on the first notification message, wherein the risk prompt information is used for prompting a user that the first notification message has risks.

In one implementation of the third aspect, the computer instructions, when executed by the processor, cause the electronic device to further perform the steps of: the electronic equipment receives a first operation of a user on the second notification message; the first operation is used for triggering the electronic equipment to display a detail page of the notification content corresponding to the first notification message; the electronic device does not respond to the first operation; or, the electronic device displays a first interface in response to the first operation, the first interface not including a detail page of notification content of the first notification message.

In one implementation of the third aspect, the computer instructions, when executed by the processor, cause the electronic device to further perform the steps of: if the text classification prediction result indicates that the first notification message is the target notification message, the electronic device closes the message pushing service of the first application.

In an implementation manner of the third aspect, the electronic device stores a preset application list, where the preset application list includes application package names of applications whose user usage frequency is less than a preset frequency; the computer instructions, when executed by the processor, cause the electronic device to further perform the steps of: if the text classification prediction result indicates that the first notification message is a target notification message, the electronic equipment acquires an application package name of the first application; and if the application package name of the first application is in the preset list, the electronic equipment uninstalls the first application.

In one implementation manner of the third aspect, when the processor executes the computer instructions, the electronic device is caused to specifically perform the following steps: if the first application is not the application downloaded by the electronic equipment from the application store, the electronic equipment acquires the attribute information of the first notification message.

In an implementation manner of the third aspect, the electronic device stores a correspondence between the notification message and the risk prompt information; when the processor executes the computer instructions, the electronic device is caused to specifically perform the steps of: if the text classification prediction result indicates that the first notification message is a target notification message, the electronic equipment acquires attribute information of risk prompt information corresponding to the first notification message; the attribute information of the risk prompt information comprises a prompt box and prompt contents; the electronic device displays a second notification message based on the prompt box and the prompt content of the risk prompt message, and the notification title and the notification content of the first notification message.

In one implementation of the third aspect, the computer instructions, when executed by the processor, cause the electronic device to further perform the steps of: the electronic equipment stores the first notification message and a text classification prediction result corresponding to the first notification message as a group of log files; if the number of the log files stored by the electronic equipment is larger than a preset number threshold, the electronic equipment sends a first notification message and a text classification prediction result corresponding to the first notification message to the server; the text classification prediction result corresponding to the first notification message is used for updating the text classification model; the electronic equipment receives the updated text classification model from the server; the updated text classification model is updated by the server through an over-the-air technology OTA.

In one implementation of the third aspect, the computer instructions, when executed by the processor, cause the electronic device to further perform the steps of: the electronic equipment combines the notification title and the notification content, and performs text vectorization processing on the combined notification title and notification content to obtain a numerical vector with a preset length.

In one implementation manner of the third aspect, when the processor executes the computer instructions, the electronic device is caused to specifically perform the following steps: the electronic device takes attribute information of the first notification message as input, operates a text classification model to obtain a text classification prediction result, and comprises: the electronic equipment takes the numerical vector with the preset length as input, operates a text classification model, and carries out vector quantity product calculation on the numerical vector with the preset length to obtain a text classification prediction result; if the vector quantity product is larger than the preset vector quantity product, the text classification prediction result indicates that the first notification message is a target notification message; wherein the value of the vector quantity product is used to characterize the frequency with which the target word appears in the first notification message.

In a fourth aspect, there is provided a computer readable storage medium having instructions stored therein which, when run on a computer, cause the computer to perform the method of any of the first aspects above.

In a fifth aspect, there is provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of any of the first aspects above.

The technical effects of any one of the design manners of the second aspect to the fifth aspect may be referred to the technical effects of the different design manners of the first aspect, and will not be repeated here.

Drawings

FIG. 1 is a schematic diagram showing a notification message displayed on a notification bar interface according to an embodiment of the present application;

FIG. 2 is a second schematic diagram of a notification message displayed on a notification bar interface according to an embodiment of the present application;

fig. 3 is a schematic hardware structure of an electronic device according to an embodiment of the present application;

fig. 4 is a schematic diagram of a software framework of an electronic device according to an embodiment of the present application;

fig. 5 is a flow chart of a method for detecting an application notification message according to an embodiment of the present application;

FIG. 6 is a schematic flow chart of model training according to an embodiment of the present application;

fig. 7 is a flowchart of another method for detecting an application notification message according to an embodiment of the present application;

FIG. 8 is a third schematic diagram of a notification message displayed on a notification bar interface according to an embodiment of the present application;

Fig. 9 is a flowchart of another method for detecting an application notification message according to an embodiment of the present application;

FIG. 10 is a diagram showing a notification message displayed on a notification bar interface according to an embodiment of the present application;

fig. 11 is a schematic structural diagram of a chip system according to an embodiment of the present application.

Detailed Description

In order that those skilled in the art will better understand the solution of the present embodiment of the present application, the technical solution of the present embodiment of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiment of the present application, and it is apparent that the described embodiment is only a part of the embodiment of the present application, not all the 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, shall fall within the scope of the application.

The terms "first" and "second" are used below for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the embodiments of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.

The notification messages disclosed by the embodiment of the application refer to various types of notification messages generated by various types of application programs installed in the electronic equipment. For example, from the application level, application update messages and push messages involving application functions may be included; specifically, according to different functions of the application, the application push message related to the application function may be a short message generated by a short message application, a push message generated by a social application (including an instant communication message, a comment message, a friend adding message, a new function recommending message, etc.), a push message generated by a shopping application (including an order stream update message, an order refund message, a new product online message, etc.), a new mail notification generated by a mail application, and other push messages generated by various applications.

In the related art, each notification message is displayed on the notification bar interface, as shown in fig. 1, which is a schematic diagram of displaying the notification message on the notification bar interface according to the embodiment of the present application, and fig. 1 is an example of a smart phone, and shows the notification message displayed on the notification bar interface. The notification content of notification messages generated by different types of application programs is different, as shown in fig. 1, and the notification messages are hot news notification messages generated by news applications; for example, the notification message is "Beijing: and (5) adjusting …% of nucleic acid negative proof time limit when entering various public places.

However, the notification content of some notification messages pushed by applications may present problems of revealing user privacy and affecting user property security. Exemplary, as shown in fig. 2, another notification message provided for the embodiment of the present application is shown in a schematic diagram of a notification bar interface, and as shown in fig. 2, the notification message is an investment financial notification message generated by a financial application; if the notification message is 'how invested in pension can maximize the benefit'; or "quick get rich in the first minute".

In the notification content of the investment management notification message, there may be information (or referred to as guiding information) for guiding the user to perform investment management. In general, since security awareness of users (especially middle-aged and elderly users) is weak, when users click on these communication messages, the users may operate according to guidance information included in the notification messages, which causes a problem of property loss (or affecting user security) of the users.

According to the scheme provided by the embodiment of the application, the notification message pushed by the application can be detected based on the text classification model, and when the notification message is detected to have the risk of revealing the privacy of the user or losing the property of the user, the electronic equipment displays the risk prompt information in the notification message in a superimposed manner and is used for prompting the user that the notification message has the risk. Under the condition that the user privacy is revealed or the user property risk is lost in the notification message, compared with the related technology, the embodiment of the application can remind the risk to the user and protect the user privacy and the property safety.

The following describes the technical scheme provided by the embodiment of the application in detail by combining the drawings of the specification.

The electronic device provided by the embodiment of the application may be a mobile phone, a smart watch, a smart bracelet, a tablet computer, a desktop, a laptop, a handheld computer, a super mobile personal computer (ultra-mobile personal computer, UMPC), a netbook, a personal digital assistant (personal digital assistant, PDA), an augmented reality (augmented reality, AR) \virtual reality (VR) device, or the like, and the embodiment of the application is not limited to the specific form of the electronic device.

As shown in fig. 3, a schematic structure of the electronic device 100 is shown. Wherein the electronic device 100 may include: processor 110, external memory interface 120, internal memory 121, universal serial bus (universal serial bus, USB) interface 130, charge management module 140, power management module 141, battery 142, antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, headset interface 170D, sensor module 180, positioning module 181, keys 190, motor 191, indicator 192, camera 193, display 194, and subscriber identity module (subscriber identification module, SIM) card interface 195, etc.

It is to be understood that the structure illustrated in the present embodiment does not constitute a specific limitation on the electronic apparatus 100. In other embodiments, electronic device 100 may include more or fewer components than shown, or certain components may be combined, or certain components may be split, or different arrangements of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The processor 110 may include one or more processing units, such as: the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), a controller, a memory, a video codec, a digital signal processor (digital signal processor, DSP), a baseband processor, and/or a neural network processor (neural-network processing unit, NPU), etc. Wherein the different processing units may be separate devices or may be integrated in one or more processors.

The controller may be a neural hub and command center of the electronic device 100. The controller can generate operation control signals according to the instruction operation codes and the time sequence signals to finish the control of instruction fetching and instruction execution.

A memory may also be provided in the processor 110 for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may hold instructions or data that the processor 110 has just used or recycled. If the processor 110 needs to reuse the instruction or data, it can be called directly from the memory. Repeated accesses are avoided and the latency of the processor 110 is reduced, thereby improving the efficiency of the system.

In some embodiments, the processor 110 may include one or more interfaces. The interfaces may include an integrated circuit (inter-integrated circuit, I2C) interface, an integrated circuit built-in audio (inter-integrated circuit sound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous receiver transmitter (universal asynchronous receiver/transmitter, UART) interface, a mobile industry processor interface (mobile industry processor interface, MIPI), a general-purpose input/output (GPIO) interface, a subscriber identity module (subscriber identity module, SIM) interface, and/or a universal serial bus (universal serial bus, USB) interface, among others.

It should be understood that the connection relationship between the modules illustrated in this embodiment is only illustrative, and does not limit the structure of the electronic device. In other embodiments, the electronic device may also use different interfacing manners in the foregoing embodiments, or a combination of multiple interfacing manners.

The charge management module 140 is configured to receive a charge input from a charger. The charger can be a wireless charger or a wired charger. In some wired charging embodiments, the charge management module 140 may receive a charging input of a wired charger through the USB interface 130. In some wireless charging embodiments, the charge management module 140 may receive wireless charging input through a wireless charging coil of the electronic device. The charging management module 140 may also supply power to the electronic device through the power management module 141 while charging the battery 142.

The power management module 141 is used for connecting the battery 142, and the charge management module 140 and the processor 110. The power management module 141 receives input from the battery 142 and/or the charge management module 140 and provides power to the processor 110, the internal memory 121, the external memory, the display 194, the camera 193, the wireless communication module 160, and the like. The power management module 141 may also be configured to monitor battery capacity, battery cycle number, battery health (leakage, impedance) and other parameters. In other embodiments, the power management module 141 may also be provided in the processor 110. In other embodiments, the power management module 141 and the charge management module 140 may be disposed in the same device.

The wireless communication function of the electronic device 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, a modem processor, a baseband processor, and the like.

The electronic device 100 implements display functions through a GPU, a display screen 194, an application processor, and the like. The GPU is a microprocessor for image processing, and is connected to the display 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. Processor 110 may include one or more GPUs that execute program instructions to generate or change display information.

The display screen 194 is used to display images, videos, and the like. The display 194 includes a display panel. The display panel may employ a liquid crystal display (liquid crystal display, LCD), an organic light-emitting diode (OLED), an active-matrix organic light emitting diode (AMOLED), a flexible light-emitting diode (FLED), a Mini-LED, a Micro-OLED, a quantum dot light-emitting diode (quantum dot light emitting diodes, QLED), or the like.

The electronic device 100 may implement photographing functions through an ISP, a camera 193, a video codec, a GPU, a display screen 194, an application processor, and the like.

The ISP is used to process data fed back by the camera 193. For example, when photographing, the shutter is opened, light is transmitted to the camera photosensitive element through the lens, the optical signal is converted into an electric signal, and the camera photosensitive element transmits the electric signal to the ISP for processing and is converted into an image visible to naked eyes. ISP can also optimize the noise, brightness and color of the image. The ISP can also optimize parameters such as exposure, color temperature and the like of a shooting scene. In some embodiments, the ISP may be provided in the camera 193.

The camera 193 is used to capture still images or video. The object generates an optical image through the lens and projects the optical image onto the photosensitive element. The photosensitive element may be a charge coupled device (charge coupled device, CCD) or a Complementary Metal Oxide Semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, which is then transferred to the ISP to be converted into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into an image signal in a standard RGB, YUV, or the like format. In some embodiments, the electronic device may include 1 or N cameras 193, N being a positive integer greater than 1.

The digital signal processor is used for processing digital signals, and can process other digital signals besides digital image signals. For example, when the electronic device selects a frequency bin, the digital signal processor is used to fourier transform the frequency bin energy, and so on.

Video codecs are used to compress or decompress digital video. The electronic device 100 may support one or more video codecs. In this way, the electronic device may play or record video in a variety of encoding formats, such as: dynamic picture experts group (moving picture experts group, MPEG) 1, MPEG2, MPEG3, MPEG4, etc.

The NPU is a neural-network (NN) computing processor, and can rapidly process input information by referencing a biological neural network structure, for example, referencing a transmission mode between human brain neurons, and can also continuously perform self-learning. Applications such as intelligent cognition of electronic devices can be realized through the NPU, for example: image recognition, face recognition, speech recognition, text understanding, etc.

The electronic device 100 may implement audio functions through an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, an application processor, and the like. Such as music playing, recording, etc.

The audio module 170 is used to convert digital audio information into an analog audio signal output and also to convert an analog audio input into a digital audio signal. The audio module 170 may also be used to encode and decode audio signals. In some embodiments, the audio module 170 may be disposed in the processor 110, or a portion of the functional modules of the audio module 170 may be disposed in the processor 110. The speaker 170A, also referred to as a "horn," is used to convert audio electrical signals into sound signals. A receiver 170B, also referred to as a "earpiece", is used to convert the audio electrical signal into a sound signal. Microphone 170C, also referred to as a "microphone" or "microphone", is used to convert sound signals into electrical signals.

The earphone interface 170D is used to connect a wired earphone. The earphone interface 170D may be a USB interface 130 or a 3.5mm open electronic device platform (open mobile terminal platform, OMTP) standard interface, a american cellular telecommunications industry association (cellular telecommunications industry association of the USA, CTIA) standard interface.

The external memory interface 120 may be used to connect an external memory card, such as a Micro SD card, to enable expansion of the memory capabilities of the electronic device. The external memory card communicates with the processor 110 through an external memory interface 120 to implement data storage functions. For example, audio, video, etc. files are stored in an external memory card.

The internal memory 121 may be used to store computer executable program code including instructions. The processor 110 executes various functional applications of the electronic device and data processing by executing instructions stored in the internal memory 121. For example, in an embodiment of the present application, the processor 110 may include a storage program area and a storage data area by executing instructions stored in the internal memory 121.

The storage program area may store an application program (such as a sound playing function, an image playing function, etc.) required for at least one function of the operating system, etc. The storage data area may store data created during use of the electronic device (e.g., audio data, phonebook, etc.), and so forth. In addition, the internal memory 121 may include a high-speed random access memory, and may further include a nonvolatile memory such as at least one magnetic disk storage device, a flash memory device, a universal flash memory (universal flash storage, UFS), and the like.

The keys 190 include a power-on key, a volume key, etc. The keys 190 may be mechanical keys. Or may be a touch key. The motor 191 may generate a vibration cue. The motor 191 may be used for incoming call vibration alerting as well as for touch vibration feedback. The indicator 192 may be an indicator light, may be used to indicate a state of charge, a change in charge, a message indicating a missed call, a notification, etc. The SIM card interface 195 is used to connect a SIM card. The SIM card may be inserted into the SIM card interface 195, or removed from the SIM card interface 195 to enable contact and separation with the electronic device. The electronic device may support 1 or N SIM card interfaces, N being a positive integer greater than 1. The SIM card interface 195 may support Nano SIM cards, micro SIM cards, and the like.

It should be understood that the illustrated structure of the embodiment of the present application does not constitute a specific limitation on the electronic device 100. In other embodiments of the application, electronic device 100 may include more or fewer components than shown, or certain components may be combined, or certain components may be split, or different arrangements of components. The illustrated components may be implemented in hardware, software, or a combination of hardware and software.

In order to make the technical solution of the present application clearer and easy to understand, the method of the embodiment of the present application is illustrated below in conjunction with a software architecture of an electronic device.

Fig. 4 is a software structure block diagram of an electronic device according to an embodiment of the present application.

The layered architecture divides the software into several layers, each with distinct roles and branches. The layers communicate with each other through a software interface. In some embodiments, android will be ^TM The system is divided into five layers, namely an application program layer, an application program framework layer, an Zhuoyun row (Android run) and system library, a hardware abstraction layer (hardware abstraction layer, HAL), a kernel layer and a driving layer from top to bottom. It should be understood that: android is used herein ^TM The system is illustrated in other operating systems (e.g., iOS ^TM System, etc.), the scheme of the present application can be implemented as long as the functions implemented by the respective functional modules are similar to those of the embodiment of the present application.

The application layer may include a series of application packages (Android application package, APK).

As shown in fig. 4, various Applications (APPs) may be installed in the application layer. Such as conversations, memos, browsers, contacts, gallery, calendar, maps, bluetooth, music, etc. In the present application, the application layer further includes an application (e.g., a first application) that pushes notification messages.

The application framework layer provides an application programming interface (application programming interface, API) and programming framework for application programs of the application layer. The application framework layer includes a number of predefined functions.

For example, the application framework layer may include a window manager, a content provider, a view system, a resource manager, a notification manager, etc., to which embodiments of the present application are not limited in any way.

The window manager is used for managing window programs. The window manager can acquire the size of the display screen, judge whether a status bar exists, lock the screen, intercept the screen and the like.

The content provider is used to store and retrieve data and make such data accessible to applications. The data may include video, images, audio, calls made and received, browsing history and bookmarks, phonebooks, etc.

The view system may be used to build a display interface for an application. Each display interface may be composed of one or more controls. In general, controls may include interface elements such as icons, buttons, menus, tabs, text boxes, dialog boxes, status bars (or notification bars), navigation bars, micro (Widget) items, and the like.

The resource manager provides various resources for the application program, such as localization strings, icons, pictures, layout files, video files, and the like.

The notification manager, using the application, can display notification information in a status bar (or notification bar), can be used to convey notification type messages, can automatically disappear after a short dwell, and does not require user interaction. Such as notification manager is used to inform that the download is complete, message alerts, etc. The notification manager may also be a notification in the form of a chart or scroll bar text that appears on the system top status bar, such as a notification of a background running application, or a notification that appears on the screen in the form of a dialog window. For example, a text message is presented in a status bar, a prompt tone is emitted, vibration is generated, and an indicator light blinks.

Android is also included in the application framework layer ^TM Basic components of the system, such as activity management services (activity manager service, AMS), package management services (package manager service, PMS), etc. In the application, android ^TM The base components of the system also include a management class (notification manager) for status bar notifications, and a system interface application (system UI manager).

The management class of status bar notification is responsible for sending notifications, clearing notifications, and the like. The system interface application is used to display status bars, notification bars, drop down menus, navigation bars, recent tasks, and the like.

As shown in fig. 4, android run includes a core library and virtual machines. Android run time is responsible for scheduling and management of the Android system.

The core library consists of two parts: one part is a function which needs to be called by java voice, and the other part is a core library of android.

The application layer and the application framework layer run in a virtual machine. The virtual machine executes java files of the application program layer and the application program framework layer as binary files. The virtual machine is used for executing the functions of object life cycle management, stack management, thread management, security and exception management, garbage collection and the like.

The system library may include a plurality of functional modules. For example: surface manager (surface manager), media Libraries (Media Libraries), three-dimensional graphics processing Libraries (e.g., openGL ES), 2D graphics engines (e.g., SGL), etc.

The surface manager is used for managing the display subsystem and providing fusion of 2D and 3D layers for a plurality of application programs. Media libraries support a variety of commonly used audio, video format playback and recording, still image files, and the like. The media library may support a variety of audio video encoding formats, such as: MPEG4, h.264, MP3, AAC, AMR, JPG, PNG, etc. The three-dimensional graphic processing library is used for realizing three-dimensional graphic drawing, image rendering, synthesis, layer processing and the like. The 2D graphics engine is a drawing engine for 2D drawing.

The hardware abstraction layer is an interface layer between the kernel layer and the hardware, and may be used to abstract the hardware. The kernel layer is located below the hardware abstraction layer and is the layer between hardware and software.

As shown in fig. 4, the driving layer at least includes a display driver, a camera driver, an audio driver, a sensor driver, and the like, which is not limited in any way according to the embodiment of the present application.

The workflow of the software system and hardware system of the electronic device 100 is illustrated below in connection with the scenario of applying push notification messages.

Referring to fig. 5, a schematic diagram of the software architecture, hardware structure, and server interaction of the electronic device 100 is shown. The embodiment of the present application is described herein with reference to the interaction diagram shown in fig. 5, which describes a software architecture, a hardware structure, and a specific implementation flow of detection of the server collaboration completion application notification message of the electronic device 100. The software architecture includes a first application in an application layer, and a management class (hereinafter referred to as notification) and a system interface application (hereinafter referred to as system UI) of status bar notifications in an application framework layer. The hardware structure mainly includes a read-only memory (ROM). Wherein the ROM stores a text classification model. As shown in fig. 5, the flow may include steps (1) - (6).

Step (1): the first application pushes a first notification message to the notification. Step (2): the ROM loads the stored text classification model into a random access memory (random access memory, RAM) for notification to detect the first notification message. On the basis, after the notification receives the first notification message of the first application, the text classification model is operated to obtain a text classification prediction result.

The text classification prediction result is used for indicating whether the first notification message is a target notification message, wherein the target notification message is a notification message with risk of revealing user privacy or losing user property.

If the text classification prediction result indicates that the first notification message is the target notification message, step (3): the notification stores the first notification message and the text classification prediction result corresponding to the first notification message as a set of log files in the ROM. Step (4): the notification system UI displays a second notification message. The second notification message comprises a notification title, notification content and risk prompt information created by notification based on the first notification message, wherein the risk prompt information is used for prompting a user that the first notification message has risks.

Step (5): and uploading the saved log file to a server by the ROM, and updating the text classification model according to the log file by the server. Step (6): the server sends the updated text classification model to the ROM.

The method provided by the embodiment of the application is exemplified below.

It should be appreciated that in Android ^TM In the system, the notification message based on the status bar notification is a global system notification, and is mainly realized through a management class (notification manager) of the status bar notification; wherein notification manager is responsible for sending or clearing notification messages.

By way of example, a notification message may be composed of the following attribute information:

Notification notification＝new NotificationCompat.Builder(context)

setContentTitle ("This is content title")// Notification title

setContentText ("This is content text")// Notification Contents

.setWhen(System.currentTimeMillis())

setSmallIcon (r.extensible. Small_icon)/notification small icon

setLargeIcon (bitmap factor. Decode resources ()), R_extensible_icon)// notify big icon

.build()；

By way of example, a notification message may consist of a notification title, notification content, a notification small icon, a notification large icon, a notification channel (channel), and so forth. Wherein the notification channel (channel) is used for managing the authority of all applications to push notification messages; when the application opens the right to push the notification message, the application can display the pushed notification message in the status bar.

Typically, the notification message displayed in the status bar by the application mainly includes a notification title and notification content, and as shown in fig. 1, the notification message includes a notification title: "today's top bar" and notification content: "Beijing: and (5) adjusting …% of nucleic acid negative proof time limit when entering various public places. Therefore, in the embodiment of the application, the notification title and the notification content included in the notification message can be trained as a group of texts to obtain a text classification model.

In the present application, a notification message in which there is a risk of revealing user privacy or losing user property may be referred to as a malicious notification message (or a target notification message as shown in the above-described embodiments of the present application), and a notification message in which there is no risk of revealing user privacy or losing user property may be referred to as a normal notification message.

On the basis, the text (i.e. sample data) of the notification message is taken as the input of the model, the classification prediction result corresponding to the label is taken as the output of the model, and model training is carried out to obtain a text classification model. Wherein in the present application, the sample data (i.e., the text of the notification message) includes the text of the malicious notification message and the text of the normal notification message. That is, the application inputs the text of the malicious notification message and the text of the normal notification message into the machine model as training samples for training.

The tag is used for indicating the occurrence frequency of the target word in the text of the malicious notification message, and the classification prediction result corresponding to the tag comprises the malicious notification message (which can be expressed as a table 1) and the normal notification message (which can be expressed as a table 0). Wherein, the target words refer to some keywords which can characterize the notification message as malicious notification message, such as "pension", "financial management", "one's own profit", and the like.

It should be understood that the foregoing is merely illustrative of target words, and that different malicious notification messages may include other target words, which is not limited in this regard by embodiments of the present application.

Fig. 6 is a schematic flow chart of model training provided in an embodiment of the present application, and exemplary, as shown in fig. 6, a text of a malicious notification message and a text of a normal notification message are used as training samples and input into a machine model for training.

It should be noted that, in the model training process, the more the number of training samples, the more accurate the model training result, i.e. the more mature the text classification model obtained by training. Therefore, to ensure accuracy of the training results, the total number of training samples is about two tens of thousands or more, and the number of each sample is not less than ten thousands. That is, the text of the malicious notification message and the text of the normal notification message are not less than ten thousand pieces, respectively.

Further, since the notification message mainly includes a notification title (content title) and notification content (content text), the inputted training samples include the notification title and the notification content. Moreover, since the notification title and the notification content belong to different texts of the training sample, data preprocessing can be performed on the training sample for training.

Firstly, combining a notification title and notification content, then carrying out text vectorization processing on the combined notification title and notification content to obtain a numerical vector with a preset length, and finally inputting the numerical vector with the preset length into a machine model for training to obtain a final text classification model.

For example, the notification title and the notification content may be combined in the form of content title/content text, and then text vectorization processing is performed on the content title/content text to obtain a numeric vector with a preset length. The text vectorization process refers to converting the combined text characters of the notification title and the notification content into numeric characters with a fixed length (i.e., the preset length).

In some embodiments, if the length of the combined notification title and text characters of the notification content is less than the fixed length, the combined notification title and text characters of the notification content may be converted to numeric characters, which may be supplemented to the fixed length with space or punctuation marks. In other embodiments, if the length of the combined notification title and text characters of the notification content is greater than the fixed length, the combined notification title and text characters of the notification content may be truncated by the fixed length, and then the truncated text characters may be converted into digital characters.

And then taking the numerical vector with the preset length as the input of the machine model, taking the classification result corresponding to the label as the output of the machine model, and running the machine model for training to obtain the text classification model. For example, assuming that the training samples include twenty-four thousands, firstly, performing text vectorization processing on the twenty-four thousands of training samples, converting the twenty-four thousands of training samples into twenty-four thousands of numerical vectors with preset lengths, and then sequentially performing vector operation on the twenty-four thousands of numerical vectors with preset lengths, namely, calculating a vector quantity product of the numerical vectors with preset lengths.

It should be appreciated that the machine model includes multiple input layers (or convolution layers) and one output layer, and after the operation of the vector number product of the numerical vector with the preset length, the machine model finally outputs a calculated vector number product. The vector quantity product of the machine model output is as follows: the machine model is based on the actual values (i.e., actual classification results) obtained after training the training samples.

On this basis, the machine model adopts an activation function (such as sigmoid) to map the actual value obtained by training between [0,1] so as to facilitate the subsequent processing. In the present application, the classification result corresponding to the tag includes table 1 and table 0. Wherein, table 1 is used for indicating that the notification message is a malicious notification message, and table 0 is used for indicating that the notification message is a normal notification message. Therefore, the machine model maps the actual value obtained by training to [0,1], and then, if the actual value is smaller than 0.5, it is expressed as table 0, and if the actual value is larger than 0.5, it is expressed as table 1.

Further, starting from the actual value obtained by training the machine model, performing inverse regression training (namely adopting a back propagation algorithm) on the machine model, and enabling the obtained actual value (namely the actual classification result) to be consistent with the classification result corresponding to the label, thereby obtaining the trained text classification model.

In the present application, the machine model may be a convolutional neural network model (convolutional neural networks, CNN), a transducer model (transformer), a support vector machine model (support vector machines, SVM), or the like, which is not limited thereto.

In the application, the text classification model can be trained through the electronic equipment, and other devices with the model training function can also be used for training the text classification model; alternatively, the text classification model may be trained by a server, which is not limited by embodiments of the present application.

In summary, the text classification model can be trained through the steps, and the trained text classification model is adopted to detect the notification message pushed by the application, so as to identify whether the notification message pushed by the application is a malicious notification message. For example, the trained text classification model can be stored in a read-only memory ROM, and when the electronic equipment is started, the text classification model stored in the ROM is loaded into the RAM to operate. On this basis, when the application pushes a message, the electronic device may run a text classification model in RAM to identify whether the notification message pushed by the application is a malicious notification message.

Fig. 7 is a schematic diagram of a method for detecting an application notification message according to an embodiment of the present application, where, as shown in fig. 7, the method may be implemented by S201-S205.

S201, the electronic equipment receives a first notification message of a first application.

Illustratively, as shown in connection with fig. 5, the first application pushes a first notification message to notification manager; accordingly, notification manager receives the first notification message of the first application.

S202, the electronic equipment acquires attribute information of the first notification message.

Wherein the attribute information of the first notification message includes a notification title and notification content of the first notification message.

For example, in connection with the above embodiment, the attribute information of the first notification message may further include a notification small icon, a notification large icon, a notification channel (channel), and the like.

In some embodiments, as shown in connection with fig. 5, the first application pushes the first notification message to notification manager, carrying the notification header and the notification content of the first notification message. Accordingly, upon receiving the first notification message of the first application at notification manager, notification manager may obtain attribute information of the first notification message, that is, obtain a notification title and notification content of the first notification message.

S203, the electronic equipment takes attribute information of the first notification message as input, and operates a text classification model to obtain a text classification prediction result; the text classification prediction result is used for indicating whether the first notification message is a target notification message or not.

Wherein the targeted notification message is a notification message that risks revealing user privacy or losing user property.

As shown in connection with fig. 5, after the first application pushes the first notification message to notification manager, the ROM loads notification manager the stored text classification model. Then, notification manager takes the attribute information of the first notification message as input, and runs the text classification model to obtain a text classification prediction result.

In some embodiments, the electronic device may pre-process the attribute information of the first notification message before entering the attribute information of the first notification message into the text classification model. For example, in combination with the above embodiment, the electronic device first combines attribute information (such as a notification header and notification content) of the first notification message, and then performs text vectorization processing on the combined notification header and notification content to obtain a numeric vector with a preset length.

Subsequently, the electronic equipment takes the numerical vector with the preset length as input, operates a text classification model, and performs vector quantity product calculation on the numerical vector with the preset length. If the vector quantity product is larger than the preset vector quantity product, the text classification prediction result indicates that the first notification message is a target notification message; if the vector quantity product is smaller than the preset vector quantity product, the text classification prediction result indicates that the first notification message is a normal notification message.

In the present application, the predetermined vector quantity product may be any value between [0,1] above, for example, 0.5. Thus, when the vector number product is greater than 0.5, it indicates that the first notification message is a target notification message (i.e., a malicious notification message); when the vector quantity product is smaller than 0.5, the first notification message is indicated to be a normal notification message.

S204, if the text classification prediction result indicates that the first notification message is a normal notification message, the electronic device displays the first notification message.

S205, if the text classification prediction result indicates that the first notification message is the target notification message, the electronic device displays the second notification message.

The second notification message comprises a notification title, notification content and risk prompt information created by the electronic device based on the first notification message, wherein the risk prompt information is used for prompting a user that the first notification message has risks.

For example, as shown in fig. 8 (1), if the text classification prediction result indicates that the first notification message is a normal notification message, the notification title and the notification content are included in the first notification message displayed by the electronic device. As shown in (2) of fig. 8, if the text classification prediction result indicates that the first notification message is the target notification message, the second notification message displayed by the electronic device includes the notification title and the notification content of the first notification message, and the risk notification information corresponding to the first notification message.

In some embodiments, the electronic device stores a correspondence between the notification message and the risk prompt message; on the basis, if the text classification result indicates that the first notification message is the target notification message, the electronic equipment acquires attribute information of risk prompt information corresponding to the first notification message. The attribute information of the risk prompt information comprises a prompt box and prompt contents.

And then, the electronic equipment creates risk prompt information based on the prompt box and prompt content of the risk prompt information. For example, in connection with the above embodiment and as shown in fig. 5, after the electronic device obtains the prompt box and the prompt content of the risk prompt, notification manager creates a function again based on the prompt box and the prompt content of the risk prompt, and writes the prompt box and the prompt content of the risk prompt into the created function again. In this way, the electronic device will display a notification message (i.e., a second notification message) that includes the risk reminder information.

In summary, in the present application, after the electronic device receives the first notification message of the first application, the electronic device obtains attribute information of the first notification message, and uses the attribute information of the first notification message as input to run the text classification model to obtain a text classification prediction result; if the text classification prediction result indicates that the first notification message is the target notification message, the electronic equipment displays a second notification message, wherein the second notification message not only comprises a notification title and notification content of the first notification message, but also comprises risk prompt information created by the electronic equipment based on the first notification message.

Typically, before an application store of an electronic device (such as a mobile phone) is put on shelf, the application is detected, such as virus searching and killing, trojan searching and killing, and the like. If the potential safety hazard of the application is detected, the application is not put on shelf in the application store. That is, applications that can be put on shelf in the application store are not hidden by security, i.e., normal applications. In the subsequent use process, the target notification message is not pushed.

Based on this, in the embodiment of the present application, as shown in fig. 9, after the first application pushes the first notification message, that is, after the electronic device receives the first notification message of the first application, the electronic device may determine whether the first application is downloaded from the application store. If the first application is not downloaded from the application store, the electronic device obtains attribute information of the first notification message so as to detect whether the first notification message is a target notification message. If the first application is downloaded from the application store, the electronic device displays a first notification message pushed by the first application.

In this way, by judging whether the first application is downloaded from the application store, if the first application is downloaded from the application store, the electronic device can normally display the first notification message pushed by the first application without executing the method of the application; if the first application is not downloaded from the application store, the electronic device executes the method of the application to identify whether the first notification message is a target notification message so as to reduce the power consumption of the device.

To further protect user privacy and property security, in some embodiments, the electronic device may be configured to not respond to user operation of the second notification message; or, the electronic device does not display the detail page of the notification content of the first notification message in response to the user's operation on the second notification message. Thus, the user cannot see the detail page of the notification content corresponding to the first notification message, and the problems of revealing the user privacy and property safety are avoided.

Taking an electronic device as an example of a mobile phone, as shown in (1) in fig. 10, the mobile phone receives a first operation of a user on a second notification message; the first operation is used for triggering the mobile phone to display a detail page of the notification content corresponding to the first notification message. In some embodiments, the mobile phone does not respond to the first operation, that is, after the mobile phone receives the first operation of the user on the second notification message, the mobile phone does not jump to the detail page of the notification content corresponding to the first notification message.

Alternatively, as shown in (2) of fig. 10, the mobile phone displays a first interface in response to the first operation. The first interface does not include a detail page of the notification content of the first notification message, i.e., the first interface is a blank page.

In combination with any of the foregoing embodiments, in some embodiments, if the electronic device identifies that the first notification message is a target notification message, that is, the text classification prediction result indicates that the first notification message is a target notification message, the electronic device closes a message push service of the first application. Therefore, the first application can not push the notification message in the using process, and the problems of revealing the privacy and property safety of the user are fundamentally solved.

For example, in combination with the above embodiment, the electronic device may close a notification channel (channel) of the first application, that is, the electronic device closes the authority of the first application to push the notification message. In this way, even if the first application pushes a notification message, the pushed notification message is not displayed in the status bar.

It should be noted that, in general, applications that are not commonly used by users are installed on the electronic device, and the applications have a high probability of pushing the target notification message. Based on this, in the embodiment of the present application, the electronic device may further store a preset application list, where the preset application list includes application package names of applications whose user usage frequency is less than the preset frequency. That is, the preset list includes application package names of applications that are not commonly used by the user.

On the basis, if the text classification prediction result indicates that the first notification message is the target notification message, the electronic equipment acquires the application package name of the first application, and matches the application package name of the first application with a preset list. And if the application package name of the first application is in the preset list, the electronic equipment uninstalls the first application.

In this embodiment, by matching the application package name of the first application with the preset list, if the application package name of the first application is in the preset list, the electronic device uninstalls the first application, that is, the electronic device uninstalls the application that is not commonly used by the user. Thus, the problems of revealing user privacy and property safety can be further avoided.

Correspondingly, in combination with any of the above embodiments, if the electronic device identifies that the first notification message is the target notification message, the electronic device stores the first notification message and the text classification prediction result corresponding to the first notification message as a set of log files. For example, the electronic device stores the log file in the ROM.

In some embodiments, if the number of log files stored by the electronic device is greater than a preset number threshold, the electronic device sends a first notification message and a text classification prediction result corresponding to the first notification message to the server. In other embodiments, the electronic device periodically sends a first notification message to the server, and a text classification prediction result corresponding to the first notification message. For example, the electronic device sends the first notification message to the server every 24 hours, or 48 hours, and the text classification prediction result corresponding to the first notification message.

The server receives a first notification message sent by the electronic device and a text classification prediction result corresponding to the first notification message, and trains and updates a text classification model based on the first notification message and the text classification prediction result corresponding to the first notification message. Subsequently, the server sends the updated text classification model to the electronic device, which is stored in the ROM.

In some embodiments, the server may update the text classification model through over-the-air technology (OTA), that is, the server updates the text classification model simultaneously when updating the system of the electronic device, without separately updating the text classification model, thereby improving the resource utilization. It should be noted that the server may update the text classification model in other ways, which are not listed here.

The above description is given by taking the example of updating the text classification model by the server, and of course, the electronic device may also update the text classification model autonomously. For example, after the electronic device saves the first notification message and the text classification prediction result corresponding to the first notification message as a set of log files, the text classification model may be updated when the electronic device is powered on (e.g., each time the electronic device is powered on).

The content described in each embodiment of the present application can explain and describe the technical solutions in other embodiments of the present application, and the technical features described in each embodiment can also be applied in other embodiments, and form new solutions in combination with the technical features in other embodiments, and the present application is only described by way of example and not by way of limitation.

An embodiment of the application provides an electronic device, which may include a display screen, a memory, and one or more processors; the memory has stored therein computer program code comprising computer instructions which, when executed by the processor, cause the electronic device to perform the functions or steps performed by the electronic device in the embodiments described above. The structure of the electronic device may refer to the structure of the electronic device 100 shown in fig. 3.

Embodiments of the present application also provide a system on a chip, as shown in FIG. 11, the system on a chip 1800 including at least one processor 1801 and at least one interface circuit 1802. The processor 1801 may be the processor 110 shown in fig. 3 in the above embodiment. Interface circuit 1802 may be, for example, an interface circuit between processor 110 and an external memory; or as an interface circuit between the processor 110 and the internal memory 121.

The processor 1801 and interface circuit 1802 described above may be interconnected by wires. For example, interface circuit 1802 may be used to receive signals from other devices (e.g., a memory of an electronic apparatus). For another example, interface circuit 1802 may be used to send signals to other devices (e.g., processor 1801). The interface circuit 1802 may, for example, read instructions stored in a memory and send the instructions to the processor 1801. The instructions, when executed by the processor 1801, may cause the electronic device to perform the steps performed by the electronic device in the embodiments described above. Of course, the system-on-chip may also include other discrete devices, which are not particularly limited in accordance with embodiments of the present application.

Embodiments of the present application also provide a computer-readable storage medium including computer instructions which, when executed on an electronic device, cause the electronic device to perform the functions or steps of the method embodiments described above.

Embodiments of the present application also provide a computer program product comprising computer instructions; when executed on an electronic device, the computer instructions cause the electronic device to perform the functions or steps of the method embodiments described above.

It will be apparent to those skilled in the art from this description that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to perform all or part of the functions described above.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another apparatus, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and the parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed in a plurality of different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a readable storage medium. Based on such understanding, the technical solution of the embodiments of the present application may be essentially or a part contributing to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, including several instructions for causing a device (may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read Only Memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely illustrative of specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present application should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for detecting an application notification message, applied to an electronic device, in which a first application is installed, the method comprising:

the electronic equipment receives a first notification message of the first application and acquires attribute information of the first notification message; wherein, the attribute information of the first notification message comprises a notification title and notification content of the first notification message;

the electronic equipment takes attribute information of the first notification message as input, and operates a text classification model to obtain a text classification prediction result; the text classification prediction result is used for indicating whether the first notification message is a target notification message, wherein the target notification message is a notification message with risk of revealing user privacy or losing user property;

if the text classification prediction result indicates that the first notification message is the target notification message, the electronic equipment displays a second notification message; the second notification message comprises a notification title, notification content and risk prompt information created by the electronic equipment based on the first notification message, wherein the risk prompt information is used for prompting a user that the first notification message has risks.

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

the electronic equipment receives a first operation of a user on the second notification message; the first operation is used for triggering the electronic equipment to display a detail page of notification content corresponding to the first notification message;

the electronic device does not respond to the first operation; or, the electronic device displays a first interface in response to the first operation, wherein the first interface does not comprise a detail page of the notification content of the first notification message.

3. The method according to claim 1 or 2, characterized in that the method further comprises:

and if the text classification prediction result indicates that the first notification message is the target notification message, the electronic equipment closes the message pushing service of the first application.

4. A method according to any of claims 1-3, wherein the electronic device stores a preset application list comprising application package names of applications that are used by a user less frequently than a preset frequency; the method further comprises the steps of:

if the text classification prediction result indicates that the first notification message is the target notification message, the electronic equipment acquires an application package name of the first application;

And if the application package name of the first application is in the preset list, the electronic equipment uninstalls the first application.

5. The method according to any one of claims 1-4, wherein the obtaining attribute information of the first notification message includes:

and if the first application is not the application downloaded by the electronic equipment from the application store, the electronic equipment acquires the attribute information of the first notification message.

6. The method of claim 1, wherein the electronic device stores a correspondence between a notification message and a risk prompt message; if the text classification prediction result indicates that the first notification message is the target notification message, the electronic device displays a second notification message, including:

if the text classification prediction result indicates that the first notification message is the target notification message, the electronic equipment acquires attribute information of risk prompt information corresponding to the first notification message; the attribute information of the risk prompt information comprises a prompt box and prompt contents;

the electronic equipment displays the second notification message based on the prompt box and the prompt content of the risk prompt information, and the notification title and the notification content of the first notification message.

7. The method according to any one of claims 1-6, further comprising:

the electronic equipment stores the first notification message and a text classification prediction result corresponding to the first notification message as a group of log files;

if the number of the log files stored by the electronic equipment is larger than a preset number threshold, the electronic equipment sends the first notification message and a text classification prediction result corresponding to the first notification message to a server; the text classification prediction result corresponding to the first notification message is used for updating the text classification model;

the electronic equipment receives the updated text classification model from the server;

the updated text classification model is updated by the server through an over-the-air technology OTA.

8. The method according to any one of claims 1-7, wherein after the electronic device obtains the attribute information of the first notification message, the method further comprises:

the electronic equipment combines the notification title and the notification content, and performs text vectorization processing on the combined notification title and the notification content to obtain a numerical vector with preset length;

The electronic device uses attribute information of the first notification message as input, operates the text classification model to obtain a text classification prediction result, and includes:

the electronic equipment takes the numerical vector with the preset length as input, operates the text classification model, and performs vector quantity product calculation on the numerical vector with the preset length to obtain the text classification prediction result;

if the vector quantity product is larger than a preset vector quantity product, the text classification prediction result indicates that the first notification message is a target notification message;

wherein the value of the vector quantity product is used to characterize the frequency with which a target word appears in the first notification message.

9. An electronic device, comprising: a display screen, a memory, and one or more processors; the display screen, the memory and the processor are coupled;

the memory is used for storing computer program codes, and the computer program codes comprise computer instructions; the computer instructions, when executed by the processor, cause the electronic device to perform the method of any one of claims 1-8.

10. A computer-readable storage medium comprising computer instructions; the computer instructions, when run on an electronic device, cause the electronic device to perform the method of any one of claims 1-8.