A network supervision method, system, medium and computing device

Abstract

The embodiments of the present invention provide a network supervision method, system, medium and computing device. The method includes: obtaining a device identification and a verification field from the received target data; wherein the device identification is an Internet of Things device that sends the target data; obtaining a pre-stored standard field that matches the device identification; comparing the verification field with the standard field to obtain a comparison result; if the comparison result indicates that the verification field is the same as the standard field, obtaining the data type from the target data; if the data type is a problem feedback type, obtaining the target problem of the Internet of Things device from the target data; determining a solution corresponding to the target problem; wherein the solution includes at least a solution algorithm and a target module for implementing the solution algorithm; controlling the target module to run the solution algorithm to solve the target problem of the Internet of Things device. The present invention reduces the risk of data transmission between Internet of Things devices and improves the reliability of the Internet of Things.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of communication technology. More specifically, embodiments of the present invention relate to a network supervision method, system, medium and computing device. Background Art

[0002] This section is intended to provide a background or context to embodiments of the invention that are recited in the claims. No description herein is admitted to be prior art by inclusion in this section.

[0003] The Internet of Things is developed on the basis of the Internet, bundling physical devices with existing IT and back-end platforms and applications, integrating different applications and systems. Due to the complexity of the IoT system, the variety of devices, and the wide exposure, it is easy for attackers to discover and exploit vulnerabilities, resulting in risks in the data transmitted between IoT devices, making the reliability of the IoT low. Summary of the invention

[0004] In this context, embodiments of the present invention are intended to provide a network supervision method, system, medium and computing device.

[0005] In a first aspect of an embodiment of the present invention, a network supervision method is provided, comprising:

[0006] Obtaining a device identification and a verification field from the received target data; wherein the device identification is the IoT device that sent the target data;

[0007] Obtaining a pre-stored standard field that matches the device identifier;

[0008] Compare the verification field with the standard field to obtain a comparison result;

[0009] If the comparison result indicates that the verification field is the same as the standard field, then obtaining a data type from the target data; wherein the data type includes at least a problem feedback type and a data transmission type;

[0010] If the data type is the problem feedback type, obtaining the target problem of the IoT device from the target data;

[0011] Determine a solution corresponding to the target problem; wherein the solution includes at least a solution algorithm and a target module for implementing the solution algorithm;

[0012] Control the target module to run the solution algorithm to solve the target problem of the Internet of Things device.

[0013] In an example of this implementation manner, if the comparison result indicates that the verification field is different from the standard field, the method further includes:

[0014] Determine that the target data is illegal data, and obtain an illegal IP address; wherein the illegal IP address is the IP address of the IoT device that sent the illegal data;

[0015] Adding the illegal IP address to an illegal database;

[0016] The illegal IP address is sent to a target IoT device with which a connection is established in advance, so that the target IoT device shields the illegal IP address.

[0017] In an embodiment of this implementation manner, if the data type is the data transmission type, the method further includes:

[0018] Acquire a data receiving device identifier and data transmission content from the target data;

[0019] Analyze the data transmission content to obtain a content analysis result;

[0020] If the content analysis result indicates that the data transmission content is qualified, the data transmission content is sent to an IoT receiving device corresponding to the data receiving device identifier.

[0021] In an embodiment of this implementation manner, the analyzing the data transmission content to obtain the content analysis result includes:

[0022] Performing semantic analysis on the data transmission content to obtain a semantic analysis result;

[0023] Determine a first confidentiality level corresponding to the semantic analysis result;

[0024] Determine a second confidentiality level corresponding to the data receiving device identifier;

[0025] If the first confidentiality level is less than or equal to the second confidentiality level, determining the data transmission content as qualified as a content analysis result;

[0026] If the first confidentiality level is greater than the second confidentiality level, the data transmission content is determined to be unqualified as a content analysis result.

[0027] In an example of this implementation manner, the performing semantic analysis on the data transmission content to obtain a semantic analysis result includes:

[0028] Performing semantic analysis on the data transmission content to determine a first semantic analysis result and a meaningful sentence;

[0029] Determining meaningless sentences from the data transmission content; wherein the meaningless sentences are all sentences in the data transmission content except the meaningful sentences;

[0030] Inputting the meaningless sentence into a pre-trained sentence connotation analysis model to obtain a second semantic analysis result corresponding to the meaningless sentence;

[0031] The first semantic analysis result and the human semantic analysis result are jointly determined as the semantic analysis result of the data transmission content.

[0032] In one embodiment of this implementation manner, the pre-stored standard field matching the device identification is constructed in the following manner:

[0033] Obtain device information of the IoT device corresponding to the device identifier; wherein the device information at least includes the device type, device identifier, and device user identifier of the IoT device;

[0034] Determine a first code corresponding to the device type;

[0035] Determine the second code corresponding to the device identifier;

[0036] Determine a third code corresponding to the device user identifier;

[0037] Determine a random number through a random function;

[0038] The first code, the second code, the third code and the random number are calculated to obtain the standard field.

[0039] In one embodiment of the present implementation, the random number is also sent to the IoT device so that the IoT device calculates the first code, the second code, and the third code corresponding to the device information and the random number to obtain the verification field.

[0040] In a second aspect of the embodiments of the present invention, a network monitoring system is provided, comprising:

[0041] A first acquisition unit is used to acquire a device identification and a verification field from the received target data; wherein the device identification is an Internet of Things device that sends the target data;

[0042] A second acquisition unit, used to acquire a pre-stored standard field that matches the device identification;

[0043] A comparison unit, used to compare the verification field with the standard field to obtain a comparison result;

[0044] A third acquisition unit, configured to acquire a data type from the target data if the comparison result indicates that the verification field is the same as the standard field; wherein the data type includes at least a problem feedback type and a data transmission type;

[0045] a fourth acquisition unit, configured to acquire a target problem of the Internet of Things device from the target data if the data type is the problem feedback type;

[0046] A determination unit, configured to determine a solution corresponding to the target problem; wherein the solution at least includes a solution algorithm and a target module for implementing the solution algorithm;

[0047] An operating unit is used to control the target module to run the solution algorithm to solve the target problem of the Internet of Things device.

[0048] In a third aspect of an embodiment of the present invention, a computing device is provided, comprising: at least one processor, a memory, and an input-output unit; wherein the memory is used to store a computer program, and the processor is used to call the computer program stored in the memory to execute any one of the methods described in the first aspect.

[0049] In a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, which includes instructions, and when the instructions are executed on a computer, the computer executes the method described in any one of the first aspects.

[0050] According to the network supervision method, system, medium and computing device of the embodiments of the present invention, it is possible to verify the verification fields in the received target data, and identify the problems of the Internet of Things devices in the target data after the verification is passed, and determine the solutions to the problems based on the problems, thereby solving the current problems based on the obtained solutions, reducing the risks of data transmission between Internet of Things devices and improving the reliability of the Internet of Things. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, in which:

[0052] Figure 1 A schematic diagram of a flow chart of a network monitoring method provided by an embodiment of the present invention;

[0053] Figure 2 A schematic diagram of the structure of a network monitoring system provided by an embodiment of the present invention;

[0054] Figure 3A schematic diagram of the structure of a medium according to an embodiment of the present invention is schematically shown;

[0055] Figure 4 A schematic diagram of the structure of a computing device according to an embodiment of the present invention is schematically shown.

[0056] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0057] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present invention, and are not intended to limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0058] Those skilled in the art will appreciate that the embodiments of the present invention may be implemented as a system, device, apparatus, method or computer program product. Therefore, the present disclosure may be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0059] According to an embodiment of the present invention, a network supervision method, system, medium and computing device are proposed.

[0060] It should be noted that any number of elements in the drawings is for illustration rather than limitation, and any naming is only for distinction and does not have any limiting meaning.

[0061] The principle and spirit of the present invention are explained in detail below with reference to several representative embodiments of the present invention.

[0062] Exemplary Methods

[0063] Reference below Figure 1 , Figure 1 This is a flow chart of a network supervision method provided by an embodiment of the present invention. It should be noted that the embodiments of the present invention can be applied to any applicable scenario.

[0064] Figure 1 The process of the network supervision method provided by an embodiment of the present invention shown includes:

[0065] Step S101, obtaining a device identification and a verification field from received target data.

[0066] In the embodiment of the present invention, the device identifier is an Internet of Things device that sends the target data.

[0067] As an optional implementation, the time when the IoT device does not send data can be recorded. If a certain IoT device does not send data continuously for a period longer than a preset period, a network communication test can be performed on the IoT device, that is, a communication test signal can be sent to the IoT device. If no feedback signal is received from the IoT device within the preset test period, it can be considered that the communication link with the IoT device is disconnected, and the network between the IoT devices needs to be repaired, thereby improving the reliability of communication with the IoT devices.

[0068] Step S102: Acquire a pre-stored standard field that matches the device identification.

[0069] In the embodiment of the present invention, the pre-stored standard field matching the device identification is constructed in the following manner:

[0070] Obtain device information of the IoT device corresponding to the device identifier; wherein the device information at least includes the device type, device identifier, and device user identifier of the IoT device;

[0071] Determine a first code corresponding to the device type;

[0072] Determine the second code corresponding to the device identifier;

[0073] Determine a third code corresponding to the device user identifier;

[0074] Determine a random number through a random function;

[0075] The first code, the second code, the third code and the random number are calculated to obtain the standard field.

[0076] Optionally, the random number is also sent to the IoT device, so that the IoT device calculates the verification field based on the first code, the second code, and the third code corresponding to the device information and the random number. In this way, the same standard field and verification field can be obtained based on the random number, ensuring the correctness of the IoT device transmitting data.

[0077] In the embodiment of the present invention, the frequency of generating random numbers may be based on a preset time interval or the number of data transmissions.

[0078] Specifically, a random number may be generated at a preset time interval (eg, 24 hours, 12 hours, etc.), and the random number may be sent to the target IoT device so that the standard field and the verification field are updated simultaneously.

[0079] It is also possible to generate a random number when the number of times the target IoT device sends data reaches a preset number (for example, 30 times, 50 times, etc.), and send the random number to the target IoT device so that the standard field and the verification field are updated at the same time.

[0080] In the embodiment of the present invention, the calculation formulas of the standard field and the verification field are the same. For example, the calculation formula may be:

[0081]

[0082] Wherein, a is the first code, b is the second code, c is the third code, β is a preset parameter, s is a random number, and Y is a standard field / verification field. The preset parameter β can be pre-stored in both the service device for calculating the standard field and the IoT device for calculating the verification field.

[0083] Step S103, comparing the verification field with the standard field to obtain a comparison result.

[0084] Step S104: if the comparison result indicates that the verification field is the same as the standard field, a data type is obtained from the target data.

[0085] In the embodiment of the present invention, the data type includes at least a problem feedback type and a data transmission type.

[0086] As an optional implementation manner, if the comparison result indicates that the verification field is different from the standard field, the following steps may also be included:

[0087] Determine that the target data is illegal data, and obtain an illegal IP address; wherein the illegal IP address is the IP address of the IoT device that sent the illegal data;

[0088] Adding the illegal IP address to an illegal database;

[0089] The illegal IP address is sent to a target IoT device with which a connection is established in advance, so that the target IoT device shields the illegal IP address.

[0090] Among them, by implementing this implementation method, when it is determined that the verification field is different from the standard field, it can be determined that the target data is not the data sent by the correct IoT device. Therefore, it is necessary to obtain the illegal IP address of the IoT device that sends the illegal data, so that each IoT device in the network supervision system stores the illegal IP address to avoid illegal operations performed by the illegal IP address, thereby damaging the IoT device and improving the security of the IoT device.

[0091] Step S105: If the data type is the problem feedback type, obtain the target problem of the IoT device from the target data.

[0092] As an optional implementation manner, if the data type is the data transmission type, the following steps may also be included:

[0093] Acquire a data receiving device identifier and data transmission content from the target data;

[0094] Analyze the data transmission content to obtain a content analysis result;

[0095] If the content analysis result indicates that the data transmission content is qualified, the data transmission content is sent to an IoT receiving device corresponding to the data receiving device identifier.

[0096] Among them, by implementing this implementation method, the data transmission content can be analyzed to obtain the content analysis result, and the data transmission content will only be sent to the Internet of Things receiving device when the content analysis result indicates that the data transmission content is qualified, thereby ensuring the accuracy of the data transmission content.

[0097] Optionally, the data transmission content is analyzed to obtain the content analysis result in the following manner:

[0098] Performing semantic analysis on the data transmission content to obtain a semantic analysis result;

[0099] Determine a first confidentiality level corresponding to the semantic analysis result;

[0100] Determine a second confidentiality level corresponding to the data receiving device identifier;

[0101] If the first confidentiality level is less than or equal to the second confidentiality level, determining the data transmission content as qualified as a content analysis result;

[0102] If the first confidentiality level is greater than the second confidentiality level, the data transmission content is determined to be unqualified as a content analysis result.

[0103] Among them, by implementing this implementation method, semantic analysis can be performed on the data transmission content to obtain the semantic information contained in the data transmission content, and the semantics can be divided into confidentiality levels. Only when the confidentiality level of the data transmission content is less than or equal to the confidentiality level of the device receiving the data transmission content, can the data transmission content be considered qualified, thereby improving the security of the transmitted data.

[0104] Specifically, the method of performing semantic analysis on the data transmission content to obtain the semantic analysis result may be:

[0105] Performing semantic analysis on the data transmission content to determine a first semantic analysis result and a meaningful sentence;

[0106] Determining meaningless sentences from the data transmission content; wherein the meaningless sentences are all sentences in the data transmission content except the meaningful sentences;

[0107] Inputting the meaningless sentence into a pre-trained sentence connotation analysis model to obtain a second semantic analysis result corresponding to the meaningless sentence;

[0108] The first semantic analysis result and the human semantic analysis result are jointly determined as the semantic analysis result of the data transmission content.

[0109] Among them, by implementing this implementation method, semantic analysis can be performed on the data transmission content, and connotation analysis can also be performed on meaningless sentences in the data transmission content, thereby preventing IoT devices from transmitting illegal content through suggestive sentences, thereby improving data security.

[0110] Step S106: determine a solution corresponding to the target problem.

[0111] In the embodiment of the present invention, the solution at least includes a solution algorithm and a target module for implementing the solution algorithm.

[0112] Step S107, controlling the target module to run the solution algorithm to solve the target problem of the IoT device.

[0113] The present invention can reduce the risk of data transmission between IoT devices and improve the reliability of IoT. In addition, the present invention can also ensure the correctness of IoT devices that transmit data. In addition, the present invention can also improve the security of IoT devices. In addition, the present invention can also ensure the accuracy of data transmission content. In addition, the present invention can also improve the security of transmitted data.

[0114] Exemplary Systems

[0115] After introducing the method of the exemplary embodiment of the present invention, next, refer to Figure 2 A network monitoring system according to an exemplary embodiment of the present invention is described. The device includes:

[0116] A first acquisition unit 201 is used to acquire a device identifier and a verification field from the received target data; wherein the device identifier is an IoT device that sends the target data;

[0117] The second acquisition unit 202 is used to acquire a pre-stored standard field that matches the device identification acquired by the first acquisition unit 201;

[0118] A comparison unit 203 is used to compare the verification field obtained by the first obtaining unit 201 with the standard field obtained by the second obtaining unit 202 to obtain a comparison result;

[0119] A third acquisition unit 204 is configured to acquire a data type from the target data if the comparison result obtained by the comparison unit 203 indicates that the verification field is the same as the standard field; wherein the data type includes at least a problem feedback type and a data transmission type;

[0120] A fourth acquisition unit 205 is configured to acquire a target problem of the IoT device from the target data if the data type acquired by the third acquisition unit 204 is the problem feedback type;

[0121] A determination unit 206 is used to determine a solution corresponding to the target problem obtained by the fourth obtaining unit 205; wherein the solution at least includes a solution algorithm and a target module for implementing the solution algorithm;

[0122] The running unit 207 is used to control the target module determined by the determining unit 206 to run the solution algorithm to solve the target problem of the Internet of Things device.

[0123] As an optional implementation manner, the third obtaining unit 204 is further configured to:

[0124] If the comparison result indicates that the verification field is different from the standard field, the target data is determined to be illegal data, and an illegal IP address is obtained; wherein the illegal IP address is the IP address of the IoT device that sent the illegal data;

[0125] Adding the illegal IP address to an illegal database;

[0126] The illegal IP address is sent to a target IoT device with which a connection is established in advance, so that the target IoT device shields the illegal IP address.

[0127] Among them, by implementing this implementation method, when it is determined that the verification field is different from the standard field, it can be determined that the target data is not the data sent by the correct IoT device. Therefore, it is necessary to obtain the illegal IP address of the IoT device that sends the illegal data, so that each IoT device in the network supervision system stores the illegal IP address to avoid illegal operations performed by the illegal IP address, thereby damaging the IoT device and improving the security of the IoT device.

[0128] As an optional implementation manner, the fourth obtaining unit 205 is further configured to:

[0129] If the data type is the data transmission type, obtaining a data receiving device identifier and data transmission content from the target data;

[0130] Analyze the data transmission content to obtain a content analysis result;

[0131] If the content analysis result indicates that the data transmission content is qualified, the data transmission content is sent to an IoT receiving device corresponding to the data receiving device identifier.

[0132] Among them, by implementing this implementation method, the data transmission content can be analyzed to obtain the content analysis result, and the data transmission content will only be sent to the Internet of Things receiving device when the content analysis result indicates that the data transmission content is qualified, thereby ensuring the accuracy of the data transmission content.

[0133] As an optional implementation manner, the fourth acquisition unit 205 analyzes the data transmission content, and the manner of obtaining the content analysis result may specifically be:

[0134] Performing semantic analysis on the data transmission content to obtain a semantic analysis result;

[0135] Determining a first confidentiality level corresponding to the semantic analysis result;

[0136] Determine a second confidentiality level corresponding to the data receiving device identifier;

[0137] If the first confidentiality level is less than or equal to the second confidentiality level, determining the data transmission content as qualified as a content analysis result;

[0138] If the first confidentiality level is greater than the second confidentiality level, the data transmission content is determined to be unqualified as a content analysis result.

[0139] Among them, by implementing this implementation method, semantic analysis can be performed on the data transmission content to obtain the semantic information contained in the data transmission content, and the semantics can be divided into confidentiality levels. Only when the confidentiality level of the data transmission content is less than or equal to the confidentiality level of the device receiving the data transmission content, can the data transmission content be considered qualified, thereby improving the security of the transmitted data.

[0140] As an optional implementation manner, the fourth acquisition unit 205 performs semantic analysis on the data transmission content, and a specific method for obtaining the semantic analysis result may be:

[0141] Performing semantic analysis on the data transmission content to determine a first semantic analysis result and a meaningful sentence;

[0142] Determining meaningless sentences from the data transmission content; wherein the meaningless sentences are all sentences in the data transmission content except the meaningful sentences;

[0143] Inputting the meaningless sentence into a pre-trained sentence connotation analysis model to obtain a second semantic analysis result corresponding to the meaningless sentence;

[0144] The first semantic analysis result and the human semantic analysis result are jointly determined as the semantic analysis result of the data transmission content.

[0145] Among them, by implementing this implementation method, semantic analysis can be performed on the data transmission content, and connotation analysis can also be performed on meaningless sentences in the data transmission content, thereby preventing IoT devices from transmitting illegal content through suggestive sentences, thereby improving data security.

[0146] As an optional implementation manner, the pre-stored standard field matching the device identification is constructed in the following manner:

[0147] Obtain device information of the IoT device corresponding to the device identifier; wherein the device information at least includes the device type, device identifier, and device user identifier of the IoT device;

[0148] Determine a first code corresponding to the device type;

[0149] Determine the second code corresponding to the device identifier;

[0150] Determine a third code corresponding to the device user identifier;

[0151] Determine a random number through a random function;

[0152] The first code, the second code, the third code and the random number are calculated to obtain the standard field.

[0153] In the embodiment of the present invention, the random number is also sent to the IoT device, so that the IoT device calculates the verification field based on the first code, the second code, and the third code corresponding to the device information and the random number. In this way, the same standard field and verification field can be obtained based on the random number, thereby ensuring the correctness of the IoT device transmitting data.

[0154] The present invention can reduce the risk of data transmission between IoT devices and improve the reliability of IoT. In addition, the present invention can also ensure the correctness of IoT devices that transmit data. In addition, the present invention can also improve the security of IoT devices. In addition, the present invention can also ensure the accuracy of data transmission content. In addition, the present invention can also improve the security of transmitted data.

[0155] Exemplary Media

[0156] After introducing the method and system of the exemplary embodiment of the present invention, next, reference is made to Figure 3 For a description of a computer-readable storage medium according to an exemplary embodiment of the present invention, please refer to Figure 3 , the computer-readable storage medium shown is a CD 30, on which a computer program (i.e., a program product) is stored. When the computer program is executed by the processor, it will implement the steps recorded in the above method implementation, for example, obtaining a device identification and a verification field from the received target data; wherein the device identification is the Internet of Things device that sends the target data; obtaining a pre-stored standard field that matches the device identification; comparing the verification field with the standard field to obtain a comparison result; if the comparison result indicates that the verification field is the same as the standard field, obtaining a data type from the target data; if the data type is a problem feedback type, obtaining a target problem of the Internet of Things device from the target data; determining a solution corresponding to the target problem; wherein the solution includes at least a solution algorithm and a target module that implements the solution algorithm; controlling the target module to run the solution algorithm to solve the target problem of the Internet of Things device; the specific implementation method of each step is not repeated here.

[0157] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0158] Exemplary Computing Devices

[0159] After introducing the method, system and medium of the exemplary embodiment of the present invention, next, reference is made to Figure 4 A computing device for network supervision according to an exemplary embodiment of the present invention.

[0160] Figure 4 A block diagram of an exemplary computing device 40 suitable for implementing embodiments of the present invention is shown, and the computing device 40 may be a computer system or a server. Figure 4 The computing device 40 shown is only an example and should not bring any limitation to the functionality and scope of use of the embodiments of the present invention.

[0161] like Figure 4As shown, the components of the computing device 40 may include, but are not limited to: one or more processors or processing units 401, a system memory 402, and a bus 403 connecting different system components (including the system memory 402 and the processing unit 401).

[0162] The computing device 40 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computing device 40, including volatile and non-volatile media, removable and non-removable media.

[0163] System memory 402 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 4021 and / or cache memory 4022. Computing device 40 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, ROM 4023 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 is not shown in the Figure 4 As shown in FIG. 4 , a disk drive for reading and writing a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 403 via one or more data medium interfaces. System memory 402 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of various embodiments of the present invention.

[0164] A program / utility 4025 having a set (at least one) of program modules 4024 may be stored, for example, in system memory 402, and such program modules 4024 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 4024 generally perform the functions and / or methods of the embodiments described herein.

[0165] The computing device 40 may also communicate with one or more external devices 404 (e.g., a keyboard, a pointing device, a display, etc.). Such communication may be performed via an input / output (I / O) interface 405. Furthermore, the computing device 40 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 406. Figure 4 As shown, the network adapter 406 communicates with other modules (such as the processing unit 401, etc.) of the computing device 40 via the bus 403. It should be understood that although Figure 4 Not shown, other hardware and / or software modules may be used in conjunction with computing device 40 .

[0166] The processing unit 401 executes various functional applications and data processing by running the program stored in the system memory 402, for example, obtaining a device identification and a verification field from the received target data; wherein the device identification is an IoT device that sends the target data; obtaining a pre-stored standard field that matches the device identification; comparing the verification field with the standard field to obtain a comparison result; if the comparison result indicates that the verification field is the same as the standard field, obtaining a data type from the target data; if the data type is a problem feedback type, obtaining a target problem of the IoT device from the target data; determining a solution corresponding to the target problem; wherein the solution includes at least a solution algorithm and a target module that implements the solution algorithm; controlling the target module to run the solution algorithm to solve the target problem of the IoT device. The specific implementation of each step will not be repeated here. It should be noted that although several units / modules or sub-units / sub-modules of the network supervision system are mentioned in the above detailed description, this division is only exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more units / modules described above can be concretized in one unit / module. On the contrary, the features and functions of one unit / module described above may be further divided into multiple units / modules to be embodied.

[0167] In the description of the present invention, it should be noted that the terms “first”, “second” and “third” are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0168] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0169] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0170] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0171] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0172] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0173] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

[0174] In addition, although the operations of the method of the present invention are described in a specific order in the drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

Claims

1. A network supervision method, comprising: Obtaining a device identification and a verification field from the received target data; wherein the device identification is the IoT device that sent the target data; Obtaining a pre-stored standard field that matches the device identifier; Compare the verification field with the standard field to obtain a comparison result; If the comparison result indicates that the verification field is the same as the standard field, then obtaining a data type from the target data; wherein the data type includes at least a problem feedback type and a data transmission type; If the data type is the problem feedback type, obtaining the target problem of the IoT device from the target data; Determine a solution corresponding to the target problem; wherein the solution includes at least a solution algorithm and a target module for implementing the solution algorithm; Controlling the target module to run the solution algorithm to solve the target problem of the IoT device; The construction method of the pre-stored standard field matching the device identification is specifically as follows: Obtain device information of the IoT device corresponding to the device identifier; wherein the device information at least includes the device type, device identifier, and device user identifier of the IoT device; Determine a first code corresponding to the device type; Determine the second code corresponding to the device identifier; Determine a third code corresponding to the device user identifier; Determine a random number through a random function; wherein the random number is also sent to the IoT device, so that the IoT device calculates the random number according to the first code, the second code, and the third code corresponding to the device information to obtain the verification field; Calculate the first code, the second code, the third code, and the random number to obtain the standard field; And, the method further comprises: When the number of received data sent by the IoT device reaches a preset number, a target random number is generated, and the target random number is sent to the IoT device, so that the standard field and the verification field are updated simultaneously; The calculation formulas of the standard field and the verification field are the same, and the calculation formula is: Among them, a is the first code, b is the second code, c is the third code, β is a preset parameter, s is the target random number, and Y is the standard field / the verification field; the preset parameter β is pre-stored in the service device for calculating the standard field and the Internet of Things device for calculating the verification field.

2. The network supervision method according to claim 1, if the comparison result indicates that the verification field is different from the standard field, the method further comprises: Determine that the target data is illegal data, and obtain an illegal IP address; wherein the illegal IP address is the IP address of the IoT device that sent the illegal data; Adding the illegal IP address to an illegal database; The illegal IP address is sent to a target IoT device with which a connection is established in advance, so that the target IoT device shields the illegal IP address.

3. The network supervision method according to claim 1, if the data type is the data transmission type, the method further comprises: Acquire a data receiving device identifier and data transmission content from the target data; Analyze the data transmission content to obtain a content analysis result; If the content analysis result indicates that the data transmission content is qualified, the data transmission content is sent to an IoT receiving device corresponding to the data receiving device identifier.

4. The network supervision method according to claim 3, wherein the step of analyzing the data transmission content to obtain the content analysis result comprises: Performing semantic analysis on the data transmission content to obtain a semantic analysis result; Determine a first confidentiality level corresponding to the semantic analysis result; Determine a second confidentiality level corresponding to the data receiving device identifier; If the first confidentiality level is less than or equal to the second confidentiality level, determining the data transmission content as qualified as a content analysis result; If the first confidentiality level is greater than the second confidentiality level, the data transmission content is determined to be unqualified as a content analysis result.

5. The network supervision method according to claim 4, wherein the step of performing semantic analysis on the data transmission content to obtain a semantic analysis result comprises: Performing semantic analysis on the data transmission content to determine a first semantic analysis result and a meaningful sentence; Determining meaningless sentences from the data transmission content; wherein the meaningless sentences are all sentences in the data transmission content except the meaningful sentences; Inputting the meaningless sentence into a pre-trained sentence connotation analysis model to obtain a second semantic analysis result corresponding to the meaningless sentence; The first semantic analysis result and the second semantic analysis result are jointly determined as the semantic analysis result of the data transmission content.

6. A network monitoring system, comprising: A first acquisition unit is used to acquire a device identification and a verification field from the received target data; wherein the device identification is an Internet of Things device that sends the target data; A second acquisition unit, used to acquire a pre-stored standard field that matches the device identification; A comparison unit, used to compare the verification field with the standard field to obtain a comparison result; A third acquisition unit, configured to acquire a data type from the target data if the comparison result indicates that the verification field is the same as the standard field; wherein the data type includes at least a problem feedback type and a data transmission type; a fourth acquisition unit, configured to acquire a target problem of the Internet of Things device from the target data if the data type is the problem feedback type; A determination unit, configured to determine a solution corresponding to the target problem; wherein the solution at least includes a solution algorithm and a target module for implementing the solution algorithm; An operation unit, used for controlling the target module to run the solution algorithm to solve the target problem of the IoT device; The construction method of the pre-stored standard field matching the device identification is specifically as follows: Obtain device information of the IoT device corresponding to the device identifier; wherein the device information at least includes the device type, device identifier, and device user identifier of the IoT device; Determine a first code corresponding to the device type; Determine the second code corresponding to the device identifier; Determine a third code corresponding to the device user identifier; Determine a random number through a random function; wherein the random number is also sent to the IoT device, so that the IoT device calculates the random number according to the first code, the second code, and the third code corresponding to the device information to obtain the verification field; Calculate the first code, the second code, the third code, and the random number to obtain the standard field; And, the first acquisition unit is further used for: When the number of received data sent by the IoT device reaches a preset number, a target random number is generated, and the target random number is sent to the IoT device, so that the standard field and the verification field are updated simultaneously; The calculation formulas of the standard field and the verification field are the same, and the calculation formula is: Among them, a is the first code, b is the second code, c is the third code, β is a preset parameter, s is the target random number, and Y is the standard field / the verification field; the preset parameter β is pre-stored in the service device for calculating the standard field and the Internet of Things device for calculating the verification field.

7. A computing device, comprising: at least one processor, memory, and input-output unit; The memory is used to store a computer program, and the processor is used to call the computer program stored in the memory to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium comprising instructions, which, when executed on a computer, causes the computer to execute the method according to any one of claims 1 to 5.

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