Safety detection method, device, electronic device and storage medium

Abstract

The embodiments of the present application disclose a security detection method, device, electronic device and storage medium. The method includes: the electronic device obtains first monitoring data collected by multiple first devices within a first preset period, then aggregates the first monitoring data to obtain second monitoring data, and then trains the basic model according to the second monitoring data to obtain a security detection model. Then, the third monitoring data collected by multiple first devices within the second preset period is obtained, and finally, the security situation within the next second preset period is predicted based on the third monitoring data and the security detection model. In the embodiments of the present application, the third monitoring data of different first devices is obtained, and the security risks that may exist in the future are predicted by using the security detection model, thereby improving the security detection effect.

Description

Technical Field

[0001] The present application relates to the field of security technology, and in particular to a security detection method, device, electronic device and storage medium. Background Art

[0002] With the development of network technology, many smart devices that can be connected to the Internet have emerged. People can use smart devices to implement some security detection functions, such as camera monitoring, infrared alarm, etc.

[0003] However, the current security detection solution is relatively simple, and the communication with any other smart devices is separate, and it only sends out an alarm to nearby people. Only when people are nearby and hear the alarm sound will emergency treatment be carried out. This will cause safety hazards when the user is not at home. Summary of the invention

[0004] The embodiments of the present application provide a security detection method, device, electronic device and storage medium. The security detection method can improve the security detection effect.

[0005] In a first aspect, an embodiment of the present application provides a security detection method, including:

[0006] Acquire first monitoring data collected by a plurality of first devices within a first preset period;

[0007] Aggregating the first monitoring data to obtain second monitoring data;

[0008] Training a basic model according to the second monitoring data to obtain a safety detection model;

[0009] Acquire third monitoring data collected by multiple first devices within a second preset period;

[0010] Predict the next safety situation within the second preset period according to the third monitoring data and the safety detection model.

[0011] In a second aspect, an embodiment of the present application provides a safety detection device, comprising:

[0012] A first acquisition module, used to acquire first monitoring data collected by multiple first devices within a first preset period;

[0013] A data processing module, used for performing aggregation processing on the first monitoring data to obtain second monitoring data;

[0014] A training module, used for training a basic model according to the second monitoring data to obtain a safety detection model;

[0015] A second acquisition module, used to acquire third monitoring data collected by multiple first devices within a second preset period;

[0016] A detection module is used to predict the safety situation within the next second preset period based on the third monitoring data and the safety detection model.

[0017] In a third aspect, an embodiment of the present application provides an electronic device comprising a memory storing executable program code and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the steps in the security detection method provided in the embodiment of the present application.

[0018] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a plurality of instructions suitable for loading by a processor to execute the steps in the security detection method provided in the embodiment of the present application.

[0019] In an embodiment of the present application, the electronic device obtains first monitoring data collected by multiple first devices within a first preset period, then aggregates the first monitoring data to obtain second monitoring data, and then trains the basic model based on the second monitoring data to obtain a security detection model. Then, the third monitoring data collected by multiple first devices within the second preset period is obtained, and finally, the security situation within the next second preset period is predicted based on the third monitoring data and the security detection model. In an embodiment of the present application, the third monitoring data of different first devices is obtained, and the security detection model is used to predict possible security risks in the future, thereby improving the security detection effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 It is a schematic diagram of the first scenario of security detection provided in an embodiment of the present application.

[0022] Figure 2 It is a first flow chart of the safety detection method provided in the embodiment of the present application.

[0023] Figure 3 It is a second flow chart of the safety detection method provided in the embodiment of the present application.

[0024] Figure 4 It is a schematic diagram of the second scenario of security detection provided in an embodiment of the present application.

[0025] Figure 5 It is a schematic diagram of the structure of the safety detection device provided in the embodiment of the present application.

[0026] Figure 6 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0028] With the development of network technology, many smart devices that can be connected to the Internet have emerged. People can use smart devices to implement some security detection functions, such as camera monitoring, infrared alarm, etc.

[0029] However, the current security detection solution is relatively simple, and the communication with any other smart devices is separate, and it only sends out an alarm to nearby people. Only when people are nearby and hear the alarm sound will emergency treatment be carried out. This will cause safety hazards when the user is not at home.

[0030] In order to solve this technical problem, the embodiments of the present application provide a security detection method, device, electronic device and storage medium. The security detection method can be applied to a variety of electronic devices, such as televisions, computers, smart phones, speakers, tablet computers, smart home devices and other electronic devices.

[0031] See also Figure 1 , Figure 1 It is a schematic diagram of the first scenario of security detection provided in an embodiment of the present application.

[0032] like Figure 1 As shown, there are often multiple electronic devices in an office or home, such as smart home devices, where A1, A2, A3, A4 and other devices are smart home devices, which can monitor the environment to obtain corresponding monitoring data. For example, a smoke sensor can obtain carbon monoxide concentration, an infrared sensor can obtain infrared intensity, an air purifier can sense air dust concentration and carbon dioxide concentration, and a fire alarm can sense temperature, etc.

[0033] The data collected by each smart home device can be uploaded to electronic device B, which can be a gateway or a server. Electronic device B can analyze the monitoring data using the security detection model corresponding to the home, and then obtain the analysis result, which can be the security result obtained by real-time monitoring of the home, or the security prediction result of the home in the future time period.

[0034] Electronic device B can also send the analysis results to a mobile terminal, such as sending the analysis results to the user's mobile phone, computer, tablet computer and other devices, so as to remind the user. In this way, even if the user is not at home or the user is not easily aware of the danger, by sending the corresponding notification reminder to the user's device, the user can promptly perceive the security risks that have occurred in the home, or the security risks that are about to occur.

[0035] See also Figure 2 , Figure 2 1 is a schematic diagram of a first process flow of a safety detection method provided in an embodiment of the present application. The safety detection method may include the following steps:

[0036] 110. Obtain first monitoring data collected by multiple first devices within a first preset period.

[0037] In some embodiments, at least one first preset period may be set, and within the first preset period, a plurality of first devices may collect corresponding first monitoring data, such as one first device collecting carbon monoxide concentration data, one first device collecting carbon dioxide concentration data, one first device collecting smoke concentration data, one first device collecting air humidity and temperature data, etc. Different first devices may collect first monitoring data of corresponding types.

[0038] In some embodiments, the environment where the multiple first devices are located can be a home, office, warehouse, etc., and the multiple first devices can be connected to the same network, and the first monitoring data collected by the multiple first devices can be sent to the outside world through the network. The multiple first devices can be connected through the Internet of Things network. When a first device is not connected to the Internet, the first monitoring data collected by the first device can be sent to another first device through the Internet of Things, and the other first device can send the first monitoring data of the first device to the outside world through the Internet.

[0039] In some embodiments, the electronic device can specify at least one second device from multiple first devices, and then control the at least one second device to obtain first monitoring data collected by other first devices except the second device, and finally the electronic device obtains the first monitoring data transmitted by the at least one second device.

[0040] For example, the second device is a device with strong networking capability, such as a network card with better performance. Or the second device is an electronic device with large storage space. For example, some first devices have limited storage space and cannot store too much first monitoring data. In this case, the designated second device can be used to store the first monitoring data.

[0041] 120. Aggregate the first monitoring data to obtain second monitoring data.

[0042] In some implementations, the electronic device may determine the data type corresponding to each first monitoring data, and then aggregate the first monitoring data according to the data type to obtain the second monitoring data.

[0043] For example, the types of first monitoring data such as carbon monoxide concentration, carbon dioxide concentration, oxygen concentration, and smoke concentration are air index type data. The carbon monoxide concentration, carbon dioxide concentration, oxygen concentration, and smoke concentration can be aggregated, for example, to generate a comprehensive air index data, which is the second monitoring data.

[0044] In some implementations, the electronic device may also determine location information of the first device corresponding to each first monitoring data, and then aggregate the first monitoring data according to the location information to obtain second monitoring data.

[0045] For example, in a home environment, some first devices are set in the kitchen, some first devices are set at the door, and some first devices are set in the living room. The electronic device can aggregate the first monitoring data collected by the first device set in the kitchen to obtain the second monitoring data. The electronic device can aggregate the first monitoring data collected by the first device set at the door to obtain the second monitoring data. The electronic device can aggregate the first monitoring data collected by the first device set in the living room to obtain the second monitoring data. In other words, the electronic device can aggregate the first monitoring data collected by the first devices that are located similarly to obtain the second monitoring data.

[0046] 130. Train the basic model according to the second monitoring data to obtain a safety detection model.

[0047] In some embodiments, after acquiring the second monitoring data, the electronic device can use the second data to train the basic model to obtain a safety detection model. The basic model can be a neural network model, and by training the neural network model, the neural network model can be trained in the direction of safety detection to obtain a safety detection model.

[0048] In some implementations, the second monitoring data may be first input into the basic model, and then the result output by the basic model may be obtained, and then the result output by the basic model may be compared with the preset result to determine whether the model needs to continue training. For example, the Euclidean distance between the result output by the basic model and the preset result may be obtained. If the Euclidean distance is less than the preset distance, it indicates that the basic model training is complete. If the Euclidean distance is greater than or equal to the preset distance, it indicates that the basic model training is not complete and further training is required.

[0049] In some embodiments, if the basic model needs to be further trained, the basic parameters of the model can be adjusted in the next round of training; or part of the data in the second monitoring data can be adjusted to change the training sample. Then the basic model is trained again until the Euclidean distance between the result output by the basic model and the preset result is less than the preset distance. At this time, it means that the basic model training is completed and the security detection model is obtained.

[0050] In some implementations, when the electronic device aggregates the first monitoring data, it can obtain different second monitoring data according to different aggregation standards. Then, the second monitoring data corresponding to different aggregation standards are used to train the basic model, and the security detection model finally trained can perform security detection from multiple dimensions.

[0051] 140. Obtain third monitoring data collected by multiple first devices within a second preset period.

[0052] In some embodiments, within the second preset period, the electronic device may obtain the third monitoring data collected by multiple first devices. For example, the electronic device may specify at least one second device from the multiple first devices, and then control the at least one second device to obtain the third monitoring data collected by other first devices except the second device, and finally the electronic device obtains the third monitoring data transmitted by the at least one second device.

[0053] For example, the second device is a device with strong networking capability, such as a network card with better performance. Or the second device is an electronic device with large storage space. For example, some first devices have limited storage space and cannot store too much third monitoring data. In this case, the designated second device can be used to store the third monitoring data.

[0054] 150. Predict the safety situation within the next second preset period based on the third monitoring data and the safety detection model.

[0055] In some embodiments, after the electronic device receives the third monitoring data, the third monitoring data is input into the security detection model, and the security detection model predicts the security situation within the next second preset period, and then sends the corresponding security situation to the target device.

[0056] For example, when the security detection model predicts that there is a security risk within the next second preset period, the electronic device will send the security risk to devices frequently used by the user, such as the user's mobile phone, computer and other devices. Even if the user is not indoors, when the user checks, he or she will know that there may be risks in the home or office and take corresponding protective measures.

[0057] In an embodiment of the present application, the electronic device obtains first monitoring data collected by multiple first devices within a first preset period, then aggregates the first monitoring data to obtain second monitoring data, and then trains the basic model based on the second monitoring data to obtain a security detection model. Then, the third monitoring data collected by multiple first devices within the second preset period is obtained, and finally, the security situation within the next second preset period is predicted based on the third monitoring data and the security detection model. In an embodiment of the present application, the third monitoring data of different first devices is obtained, and the security detection model is used to predict possible security risks in the future, thereby improving the security detection effect.

[0058] See also Figure 2 , Figure 2 1 is a second flow chart of the safety detection method provided in the embodiment of the present application. The safety detection method may include the following steps:

[0059] 210. Determine at least one second device from multiple first devices.

[0060] In some embodiments, within the first preset period, multiple first devices may collect corresponding first monitoring data, such as one first device collecting carbon monoxide concentration data, one first device collecting carbon dioxide concentration data, one first device collecting smoke concentration data, one first device collecting air humidity and temperature data, etc. Different first devices may collect first monitoring data of corresponding types.

[0061] However, some first devices cannot connect to the Internet, or the storage space of some first devices is too small to store data. Therefore, it is necessary to determine at least one second device among multiple first devices, which has the ability to connect to the Internet and has a large storage space, which can store the first monitoring data of multiple other first devices and the first monitoring data detected by itself.

[0062] 202. Control at least one second device to obtain first monitoring data collected by a first device other than the second device.

[0063] In some implementations, the second device can directly obtain the first monitoring data collected by itself, or the second device can obtain the first monitoring data collected by other first devices other than itself through an Internet of Things connection, or through a transmission method such as Bluetooth, WiFi, etc. Then, the first monitoring data is stored in its own storage chip.

[0064] Among them, when there are not many first devices, only one second device can be designated to obtain the first monitoring data collected by other first devices. When there are many first devices, if only one second device is designated to obtain the first monitoring data collected by other first devices, the second device may have insufficient storage space. Therefore, multiple second devices can be designated to obtain the first monitoring data collected by other first devices.

[0065] 203. Obtain first monitoring data transmitted by at least one second device.

[0066] In some embodiments, after determining the second device, the electronic device can directly obtain the first monitoring data obtained by the first device within the first preset period from at least one second device. For example, the second device compresses the first monitoring data that does not correspond to the first device to obtain a compressed package, and then quickly transmits the compressed package to the electronic device.

[0067] Alternatively, the second device may associate each first device with its corresponding first monitoring data to obtain an association table, and then directly send all the first monitoring data to the electronic device, and send the association table to the electronic device at the same time, so that the electronic device finally obtains the first monitoring data corresponding to each first device.

[0068] In some implementations, after acquiring the first monitoring data, the electronic device may determine whether any parameter value of the first monitoring data is greater than a corresponding preset parameter value.

[0069] If the parameter value of any first monitoring data is greater than the corresponding preset parameter value, the first monitoring data collected by multiple first devices in the next first preset period will be acquired. For example, when the humidity value in the air is greater than the preset humidity value, or the carbon monoxide concentration value is greater than the preset concentration value, the first monitoring data collected by multiple first devices in the next first preset period will be acquired.

[0070] If the parameter value of any first monitoring data is less than or equal to the corresponding preset parameter value, then within the first preset period, the first monitoring data acquired by each first device is continuously acquired until the time reaches the end of the first preset period.

[0071] In some embodiments, the sum value range corresponding to all first monitoring data in a first preset period under normal conditions can be determined, for example, the temperature value plus the humidity value plus the carbon monoxide concentration value and other data, to obtain the first sum value under normal conditions. And the ratio of each first monitoring data to the first sum value under normal conditions is determined to obtain the preset ratio value corresponding to each first monitoring data.

[0072] The second sum value of all the first monitoring data in the current first preset period is obtained, and then the ratio of each first monitoring data to the second sum value in the current period is determined to obtain the target ratio corresponding to each first monitoring data.

[0073] Then, the target ratio corresponding to each first monitoring data is compared with the preset ratio. If the target ratio is greater than the preset ratio, the first monitoring data collected by the first devices in the next first preset period is acquired.

[0074] 204. Determine a data type corresponding to each first monitoring data.

[0075] There are multiple data types in the first monitoring data acquired by the electronic device. For example, the types of first monitoring data such as carbon monoxide concentration, carbon dioxide concentration, oxygen concentration, and smoke concentration are air indicator type data. Infrared intensity, ultraviolet intensity, light intensity, etc. belong to light type data. Temperature, humidity, etc. belong to somatosensory type data.

[0076] The electronic device may classify each first monitoring data according to the data type to which each first monitoring data belongs.

[0077] 205. Aggregate the first monitoring data according to the data type to obtain second monitoring data.

[0078] The electronic device can aggregate the carbon dioxide concentration, carbon dioxide concentration, oxygen concentration, and smoke concentration to generate a comprehensive air index data, which is the second monitoring data. Alternatively, the first monitoring data such as infrared intensity, ultraviolet intensity, and light intensity can be aggregated to obtain the second monitoring data.

[0079] 206. Train the basic model according to the second monitoring data to obtain a safety detection model.

[0080] In some embodiments, after acquiring the second monitoring data, the electronic device can use the second data to train the basic model to obtain a safety detection model. The basic model can be a neural network model, and by training the neural network model, the neural network model can be trained in the direction of safety detection to obtain a safety detection model.

[0081] In some implementations, the second monitoring data may be first input into the basic model, and then the result output by the basic model may be obtained, and then the result output by the basic model may be compared with the preset result to determine whether the model needs to continue training. For example, the Euclidean distance between the result output by the basic model and the preset result may be obtained. If the Euclidean distance is less than the preset distance, it indicates that the basic model training is complete. If the Euclidean distance is greater than or equal to the preset distance, it indicates that the basic model training is not complete and further training is required.

[0082] In some embodiments, if the basic model needs to be further trained, the basic parameters of the model can be adjusted in the next round of training; or part of the data in the second monitoring data can be adjusted to change the training sample. Then the basic model is trained again until the Euclidean distance between the result output by the basic model and the preset result is less than the preset distance. At this time, it means that the basic model training is completed and the security detection model is obtained.

[0083] In some implementations, when the electronic device aggregates the first monitoring data, it can obtain different second monitoring data according to different aggregation standards. Then, the second monitoring data corresponding to different aggregation standards are used to train the basic model, and the security detection model finally trained can perform security detection from multiple dimensions.

[0084] 207. Obtain third monitoring data collected by multiple first devices within a second preset period.

[0085] In some embodiments, the electronic device is provided with a second preset period, and within the second preset period, the electronic device can obtain the second monitoring data collected by multiple first devices. For example, the electronic device can specify at least one second device from multiple first devices, and then control the at least one second device to obtain the third monitoring data collected by other first devices except the second device, and finally the electronic device obtains the third monitoring data transmitted by the at least one second device.

[0086] For example, the second device is a device with strong networking capability, such as a network card with better performance. Or the second device is an electronic device with large storage space. For example, some first devices have limited storage space and cannot store too much third monitoring data. In this case, the designated second device can be used to store the third monitoring data.

[0087] 208. Normalize the third monitoring data to obtain normalized monitoring data.

[0088] For example, after acquiring the third monitoring data, the electronic device may add all the third monitoring data to obtain a third sum value, and then divide each third monitoring data by the third sum value to obtain normalized monitoring data corresponding to each third monitoring data.

[0089] In this way, the differences between different third monitoring data can be eliminated, and the obtained normalized monitoring data are under the same quantitative standard. When the security detection model processes the normalized monitoring data, the corresponding results can be predicted more accurately.

[0090] 209. Input the normalized monitoring data into the safety detection model to predict the safety situation within the next second preset period.

[0091] In some embodiments, after the electronic device receives the normalized monitoring data, the normalized monitoring data is input into a safety detection model, and the safety detection model predicts the safety situation within the next second preset period.

[0092] 210. If the security detection model predicts that there is a security risk within the next second preset period, a detection result indicating that there is a security risk within the next second preset period is sent to the target device.

[0093] For example, when the security detection model predicts that there is a security risk within the next second preset period, the electronic device will send the security risk to devices frequently used by the user, such as the user's mobile phone, computer and other devices. Even if the user is not indoors, when the user checks, he or she will know that there may be risks in the home or office and take corresponding protective measures.

[0094] In the embodiment of the present application, at least one second device is determined from among a plurality of first devices, and then at least one second device is controlled to obtain first monitoring data collected by first devices other than the second device, and first monitoring data transmitted by at least one second device is obtained, and the data type corresponding to each first monitoring data is determined. The first monitoring data is then aggregated according to the data type to obtain second monitoring data, and the basic model is trained according to the second monitoring data to obtain a security detection model.

[0095] Then, the third monitoring data collected by the multiple first devices within the second preset period is obtained, and the third monitoring data is normalized to obtain normalized monitoring data. The normalized monitoring data is input into the security detection model to predict the security situation within the next second preset period. If the security detection model predicts that there is a security risk within the next second preset period, the detection result of the security risk within the next second preset period is sent to the target device. This achieves the prediction of future risks and improves the security detection effect. It enables users to take corresponding protective measures.

[0096] For a more detailed understanding of the safety detection method provided in the embodiments of the present application, please continue to refer to Figure 4 , Figure 4 It is a schematic diagram of the second scenario of the security detection method provided in the embodiment of the present application.

[0097] like Figure 4 As shown, a plurality of first devices are provided at the node layer, and the first devices can obtain the third monitoring data of the current environment, and then send the third monitoring data to the gateway layer. The gateway corresponding to the gateway layer can be used as an electronic device to process the third monitoring data. Alternatively, the gateway layer directly sends the third monitoring data to the server layer, and the server corresponding to the server layer inputs the third monitoring data into the security detection model, and then obtains the security situation corresponding to the current environment in the next second preset period. If there is a security risk within the next second preset period, the server will send a security reminder message to the target device to remind the user to take security protection measures.

[0098] See also Figure 5 , Figure 5 : is a schematic diagram of the structure of a safety detection device provided in an embodiment of the present application. The safety detection device comprises:

[0099] The first acquisition module 310 is used to acquire first monitoring data collected by multiple first devices within a first preset period.

[0100] The first acquisition module 310 is further used to determine at least one second device from multiple first devices; control at least one second device to acquire first monitoring data collected by first devices other than the second device; and acquire first monitoring data transmitted by at least one second device.

[0101] The first acquisition module 310 is also used to determine whether the parameter value of any first monitoring data is greater than the corresponding preset parameter value before acquiring the first monitoring data transmitted by at least one second device; if the parameter value of any first monitoring data is greater than the corresponding preset parameter value, then start acquiring the first monitoring data collected by multiple first devices in the next first preset period.

[0102] The data processing module 320 is used to aggregate the first monitoring data to obtain second monitoring data;

[0103] The data processing module 320 is further used to determine the data type corresponding to each first monitoring data; and perform aggregation processing on the first monitoring data according to the data type to obtain second monitoring data.

[0104] The data processing module 320 is further used to determine the location information of the first device corresponding to each first monitoring data; and aggregate the first monitoring data according to the location information to obtain second monitoring data.

[0105] The training module 330 is used to train the basic model according to the second monitoring data to obtain a safety detection model.

[0106] The second acquisition module 340 is used to acquire third monitoring data collected by multiple first devices within a second preset period.

[0107] The detection module 350 is used to predict the safety situation within the next second preset period according to the third monitoring data and the safety detection model.

[0108] The detection module 350 is also used to normalize the third monitoring data to obtain normalized monitoring data; and input the normalized monitoring data into the safety detection model to predict the safety situation within the next second preset period.

[0109] The detection module 350 is also used to predict the security situation within the next second preset period based on the third monitoring data and the security detection model. If the security detection model predicts that there is a security risk within the next second preset period, the detection result of the security risk within the next second preset period is sent to the target device.

[0110] In an embodiment of the present application, the electronic device obtains first monitoring data collected by multiple first devices within a first preset period, then aggregates the first monitoring data to obtain second monitoring data, and then trains the basic model based on the second monitoring data to obtain a security detection model. Then, the third monitoring data collected by multiple first devices within the second preset period is obtained, and finally, the security situation within the next second preset period is predicted based on the third monitoring data and the security detection model. In an embodiment of the present application, the third monitoring data of different first devices is obtained, and the security detection model is used to predict possible security risks in the future, thereby improving the security detection effect.

[0111] Accordingly, the present application also provides an electronic device, such as Figure 6 As shown, the electronic device may include an input unit 401, a display unit 402, a memory 403 including one or more computer-readable storage media, a sensor 405, a processor 404 including one or more processing cores, and a power supply 406. Those skilled in the art will appreciate that Figure 6 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0112] The input unit 401 can be used to receive input digital or character information, and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control. Specifically, in a specific embodiment, the input unit 401 may include a touch-sensitive surface and other input devices. The touch-sensitive surface, also known as a touch display screen or a touchpad, can collect the user's touch operations on or near it (such as the user's operation on or near the touch-sensitive surface using any suitable object or accessory such as a finger, a stylus, etc.), and drive the corresponding connection device according to a pre-set program. Optionally, the touch-sensitive surface may include a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into the touch point coordinates, and then sends it to the processor 404, and can receive and execute the command sent by the processor 404. In addition, the touch-sensitive surface can be implemented using multiple types such as resistive, capacitive, infrared and surface acoustic waves. In addition to the touch-sensitive surface, the input unit 401 may also include other input devices. Specifically, other input devices may include, but are not limited to, one or more of a physical keyboard, function keys (such as a volume control key, a switch key, etc.), a trackball, a mouse, a joystick, and the like.

[0113] The display unit 402 can be used to display information input by the user or information provided to the user and various graphical user interfaces of the electronic device, which can be composed of graphics, text, icons, videos and any combination thereof. The display unit 402 may include a display panel. Optionally, the display panel may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), etc. Further, the touch-sensitive surface may cover the display panel. When the touch-sensitive surface detects a touch operation on or near it, it is transmitted to the processor 404 to determine the type of touch event. Subsequently, the processor 404 provides a corresponding visual output on the display panel according to the type of touch event. Although in Figure 6 In the embodiment, the touch-sensitive surface and the display panel are used as two independent components to realize input and output functions, but in some embodiments, the touch-sensitive surface and the display panel can be integrated to realize input and output functions.

[0114] The memory 403 can be used to store software programs and modules, and the processor 404 executes various functional applications and data processing by running the software programs and modules stored in the memory 403. The memory 403 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device (such as audio data, a phone book, etc.), etc. In addition, the memory 403 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 403 may also include a memory controller to provide the processor 404 and the input unit 401 with access to the memory 403.

[0115] The electronic device may also include at least one sensor 405, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel according to the brightness of the ambient light, and the proximity sensor may turn off the display panel and / or backlight when the electronic device is moved to the ear. As a type of motion sensor, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that identify the posture of the electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; as for other sensors that can be configured in the electronic device, such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., they will not be repeated here.

[0116] The processor 404 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 403 and calling data stored in the memory 403, it performs various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 404 may include one or more processing cores; preferably, the processor 404 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 404.

[0117] The electronic device also includes a power supply 406 (such as a battery) for supplying power to various components. Preferably, the power supply can be logically connected to the processor 404 through a power management system, so that the power management system can manage charging, discharging, power consumption and other functions. The power supply 406 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.

[0118] Although not shown, the electronic device may also include a camera, a Bluetooth module, etc., which will not be described in detail here. Specifically in this embodiment, the processor 404 in the electronic device will load the executable files corresponding to the processes of one or more applications into the memory 403 according to the following instructions, and the processor 404 will run the applications stored in the memory 403 to achieve various functions:

[0119] Acquire first monitoring data collected by a plurality of first devices within a first preset period;

[0120] Aggregate the first monitoring data to obtain second monitoring data;

[0121] The basic model is trained according to the second monitoring data to obtain a safety detection model;

[0122] Acquire third monitoring data collected by multiple first devices within a second preset period;

[0123] The safety situation within the next second preset period is predicted based on the third monitoring data and the safety detection model.

[0124] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0125] To this end, an embodiment of the present application provides a computer-readable storage medium, in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any security detection method provided in the embodiment of the present application. For example, the instructions can execute the following steps:

[0126] Acquire first monitoring data collected by a plurality of first devices within a first preset period;

[0127] Aggregate the first monitoring data to obtain second monitoring data;

[0128] The basic model is trained according to the second monitoring data to obtain a safety detection model;

[0129] Acquire third monitoring data collected by multiple first devices within a second preset period;

[0130] The safety situation within the next second preset period is predicted based on the third monitoring data and the safety detection model.

[0131] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0132] The computer-readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0133] Since the instructions stored in the storage medium can execute the steps in any security detection method provided in the embodiments of the present application, the beneficial effects that can be achieved by any security detection method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0134] The above is a detailed introduction to a security detection method, device, electronic device and storage medium provided in the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A safety detection method, characterized in that: include: Acquire first monitoring data collected by a plurality of first devices within a first preset period; Aggregating the first monitoring data to obtain second monitoring data; Training a basic model according to the second monitoring data to obtain a safety detection model; Acquire third monitoring data collected by multiple first devices within a second preset period; Predicting the safety situation within the next second preset period according to the third monitoring data and the safety detection model; The obtaining of first monitoring data collected by a plurality of first devices within a first preset period includes: Determine at least one second device from the plurality of first devices; the at least one second device is a device with Internet connection capability among the plurality of first devices, and the storage space of the at least one second device is capable of storing the first monitoring data of the first devices other than the second device and the first monitoring data of the second device itself; Controlling the at least one second device to obtain the first monitoring data collected by the first device except the second device; when the first device is not connected to the Internet, the first monitoring data collected by the first device is sent to the at least one second device through the Internet of Things; Acquire the first monitoring data transmitted by the at least one second device.

2. The safety detection method according to claim 1, characterized in that: Before acquiring the first monitoring data transmitted by the at least one second device, the method further includes: Determining whether any parameter value of the first monitoring data is greater than a corresponding preset parameter value; If the parameter value of any of the first monitoring data is greater than the corresponding preset parameter value, the first monitoring data collected by the plurality of first devices in the next first preset period starts to be acquired.

3. The safety detection method according to claim 1, characterized in that: The aggregating the first monitoring data to obtain second monitoring data includes: Determine a data type corresponding to each of the first monitoring data; The first monitoring data is aggregated according to the data type to obtain the second monitoring data.

4. The safety detection method according to claim 1, characterized in that: The aggregating the first monitoring data to obtain second monitoring data includes: Determine location information of a first device corresponding to each of the first monitoring data; The first monitoring data is aggregated according to the location information to obtain the second monitoring data.

5. The safety detection method according to any one of claims 1 to 4, characterized in that: The predicting the safety situation within the next second preset period according to the third monitoring data and the safety detection model includes: Normalizing the third monitoring data to obtain normalized monitoring data; The normalized monitoring data is input into the safety detection model to predict the safety situation within the next second preset period.

6. The safety detection method according to any one of claims 1 to 4, characterized in that: After predicting the safety situation within the next second preset period according to the third monitoring data and the safety detection model, the method further includes: If the security detection model predicts that there is a security risk within the next second preset period, the detection result of the security risk within the next second preset period is sent to the target device.

7. A safety detection device, characterized in that: include: A first acquisition module, used to acquire first monitoring data collected by multiple first devices within a first preset period; A data processing module, used for performing aggregation processing on the first monitoring data to obtain second monitoring data; A training module, used for training a basic model according to the second monitoring data to obtain a safety detection model; A second acquisition module, used to acquire third monitoring data collected by multiple first devices within a second preset period; A detection module, used for predicting the safety situation within the next second preset period according to the third monitoring data and the safety detection model; The first acquisition module is also used for: Determine at least one second device from the plurality of first devices; the at least one second device is a device with Internet connection capability among the plurality of first devices, and the storage space of the at least one second device is capable of storing the first monitoring data of the first devices other than the second device and the first monitoring data of the second device itself; Controlling the at least one second device to obtain first monitoring data collected by the first device except the second device; When the first device is not connected to the Internet, the first monitoring data collected by the first device is sent to the at least one second device through the Internet of Things; Acquire the first monitoring data transmitted by the at least one second device.

8. An electronic device, characterized in that: include: A memory storing executable program code, and a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the steps in the security detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute the steps in the security detection method according to any one of claims 1 to 6.

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