Disclosure of Invention
In view of this, the present application provides a virtual machine-based virus reporting method and apparatus, a storage medium, and a computer device.
According to one aspect of the application, a virus reporting method based on a virtual machine is provided, and comprises the following steps:
executing a target program to be detected in the virtual machine;
monitoring at least one virus reporting monitoring point in the execution process of the target program, and recording the use condition of the at least one virus reporting monitoring point in the execution process of the target program;
and judging whether the target program is a virus program or not according to the use condition of the target program on the virus reporting monitoring point.
Specifically, the determining, according to the usage of the target program to the virus reporting monitoring point, whether the target program is a virus program specifically includes:
calculating a virus detection value of the target program according to the use condition of the target program to the virus reporting monitoring points and the virus reporting experience value of each virus reporting monitoring point;
and if the virus detection value of the target program is greater than or equal to a preset virus empirical value, determining that the target program is a virus program.
Specifically, the method further comprises:
and if the virus detection value of the target program is smaller than the preset virus empirical value, determining that the target program is not a virus program.
Specifically, before executing the target program to be detected in the virtual machine, the method further includes:
acquiring behavior characteristics corresponding to a plurality of virus samples;
and determining the virus reporting monitoring points and the virus reporting experience values of the virus reporting monitoring points according to the behavior characteristics corresponding to the plurality of virus samples.
Specifically, the determining the virus reporting monitoring point and the virus reporting experience value of the virus reporting monitoring point according to the behavior characteristics corresponding to the plurality of virus samples specifically includes:
analyzing virus reporting key behavior characteristics of the plurality of virus samples and key weights of the virus reporting key behavior characteristics according to behavior characteristics corresponding to the plurality of virus samples and preset safety program behavior characteristics;
and determining a calling function corresponding to the key behavior characteristics of the virus reporting as the virus reporting monitoring point, and determining the key weight of the key behavior characteristics of the virus reporting as the virus reporting experience value of the virus reporting monitoring point.
Specifically, after determining that the target program is a virus program, the method further includes:
and adding the target program into a virus program library.
Specifically, the method further comprises:
and when the number of the virus programs in the virus program library exceeds a preset number threshold, acquiring behavior characteristics corresponding to the virus programs in the virus program library, and updating the virus reporting monitoring points and the virus reporting experience values of the virus reporting monitoring points according to the behavior characteristics.
According to another aspect of the present application, there is provided a virtual machine-based poison reporting apparatus, including:
the target program execution module is used for executing a target program to be detected in the virtual machine;
the monitoring module is used for monitoring at least one virus reporting monitoring point in the execution process of the target program and recording the use condition of the at least one virus reporting monitoring point in the execution process of the target program;
and the virus detection module is used for judging whether the target program is a virus program according to the use condition of the target program on the virus reporting monitoring point.
Specifically, the virus detection module specifically includes:
the detection value calculation unit is used for calculating the virus detection value of the target program according to the use condition of the target program on the virus reporting monitoring points and the virus reporting experience value of each virus reporting monitoring point;
and the virus program detection unit is used for determining that the target program is a virus program if the virus detection value of the target program is greater than or equal to a preset virus empirical value.
Specifically, the apparatus further comprises:
and the safety program detection unit is used for determining that the target program is not the virus program if the virus detection value of the target program is smaller than the preset virus empirical value.
Specifically, the apparatus further comprises:
the behavior characteristic acquisition module is used for acquiring behavior characteristics corresponding to a plurality of virus samples before executing a target program to be detected in the virtual machine;
and the monitoring point determining module is used for determining the virus reporting monitoring points and the virus reporting experience values of the virus reporting monitoring points according to the behavior characteristics corresponding to the plurality of virus samples.
Specifically, the monitoring point determining module specifically includes:
the weight determining unit is used for analyzing the virus reporting key behavior characteristics of the plurality of virus samples and the key weight of the virus reporting key behavior characteristics according to the behavior characteristics corresponding to the plurality of virus samples and the preset safety program behavior characteristics;
and the empirical value determining unit is used for determining a calling function corresponding to the key behavior characteristics of the virus reporting as the virus reporting monitoring point and determining the key weight of the key behavior characteristics of the virus reporting as the virus reporting empirical value of the virus reporting monitoring point.
Specifically, the apparatus further comprises:
and the virus library establishing module is used for adding the target program into the virus library after determining that the target program is the virus program.
Specifically, the apparatus further comprises:
and the monitoring point updating module is used for acquiring the behavior characteristics corresponding to the virus programs in the virus program library when the number of the virus programs in the virus program library exceeds a preset number threshold, and updating the virus reporting monitoring points and the virus reporting experience values of the virus reporting monitoring points according to the behavior characteristics.
According to yet another aspect of the present application, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the virtual machine-based virus notification method described above.
According to yet another aspect of the present application, there is provided a computer device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, the processor implementing the virtual machine based virus notification method when executing the program.
By means of the technical scheme, the virtual machine based virus reporting method and device, the storage medium and the computer equipment record the use condition of the target program needing virus detection to the virus reporting monitoring point in the execution process by using the virtual machine technology, then perform heuristic virus checking and killing on the use condition of the virus reporting monitoring point according to the extracted target program, and detect whether the target program is a virus program. The method and the system utilize the virtual machine technology, not only can effectively obtain the running record of the target program when the target program is executed in the virtual machine, but also can not influence the real computer environment to protect the safety of the computer, and simultaneously, heuristic virus detection is carried out based on the running record of the target program, so that the method and the system are helpful for improving the detection rate of unknown viruses such as novel viruses and variant viruses.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Detailed Description
The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
In this embodiment, a virus reporting method based on a virtual machine is provided, as shown in fig. 1, the method includes:
step 101, executing a target program to be detected in a virtual machine;
102, monitoring at least one virus reporting monitoring point in the execution process of the target program, and recording the use condition of the at least one virus reporting monitoring point in the execution process of the target program;
and 103, judging whether the target program is a virus program according to the use condition of the target program to the virus reporting monitoring point.
In the prior art, a virus library established in advance is usually used, and virus feature matching is performed on features of a program to be detected according to virus features contained in a virus program stored in the virus library, and if the features of the program to be detected hit the virus library, the program is a virus-carrying program. If new viruses or variant viruses appear, the viruses are difficult to accurately detect by using the original virus library, and the defense on unknown viruses cannot be realized.
In order to solve the above-mentioned defects in the prior art, in the embodiment of the present application, heuristic virus checking is adopted, where heuristic virus checking refers to determining whether a program to be detected is a virus-carrying program by using an execution characteristic exhibited by the program in an execution process. Specifically, the general characteristics of the execution behaviors of the virus program are analyzed, and then virus detection is performed according to the general execution characteristics of the virus program. For example, a virus program writes a file into a system directory, reads and writes a boot area, writes a registry boot entry, opens another process, reads and writes another process, dynamically loads a DLL, and dynamically obtains an API address, and for a family virus, there may be a series of execution features that refer to the same library function, use the same icon, use a more unique import module, and so on.
In addition, in the existing method for acquiring the execution characteristics of the target program, a mode of injecting a DLL into the target process and monitoring a calling function in the DLL is generally adopted, and this mode mainly has two defects that the target process may have countermeasure means such as injection prevention and API hook prevention to prevent an execution sequence from being acquired, and the target process may have an influence on a real computer environment, and the computer system may be infected by a virus while the virus is found.
In order to overcome the defect of obtaining the execution characteristics, in the embodiment of the present application, a virtual machine technology is used, and an object program that needs to be subjected to virus detection is placed in a virtual machine for execution, because the virtual machine is a simulation of a real computer, if the object program calls a function when executed in the real computer, a stub function corresponding to the function is called when executed in the virtual machine, and therefore, an operation record of the object program when executed in the virtual machine can reflect an operation record of the object program when executed in the real computer. The running record of the virtual machine when the target program is executed can be effectively obtained, and the real computer environment cannot be influenced, so that the safety of the computer is protected.
With reference to the above description, in steps 101 to 103, first, an executable target program is allocated to a virtual machine, the virtual machine loads and runs the target program, and meanwhile, in an execution process of the target program, at least one pre-defined virus reporting monitoring point is monitored, where the virus reporting monitoring point is a unit in the virtual machine that is usually used in the execution process of the virus program, and specifically, the virus reporting monitoring point may be a stub function in the virtual machine, and if the virus reporting monitoring point is used in the execution process of the target program, the log is recorded, and then, according to a usage situation of the virus reporting monitoring point in the execution process of the virtual machine by the target program, whether the target program is a virus program is analyzed, for example, if a certain target program uses most of the pre-agreed virus reporting monitoring points in the execution process of the target program, the target program is likely to be a virus program, the virus detection based on the virtual machine is realized through the method.
By applying the technical scheme of the embodiment, the virtual machine technology is utilized to record the use condition of the virus reporting monitoring point in the execution process of the target program needing virus detection, and then the heuristic virus checking and killing is carried out on the use condition of the virus reporting monitoring point according to the extracted target program to detect whether the target program is a virus program. The method and the system utilize the virtual machine technology, not only can effectively obtain the running record of the target program when the target program is executed in the virtual machine, but also can not influence the real computer environment to protect the safety of the computer, and simultaneously, heuristic virus detection is carried out based on the running record of the target program, so that the method and the system are helpful for improving the detection rate of unknown viruses such as novel viruses and variant viruses.
Further, as a refinement and an extension of the specific implementation of the above embodiment, in order to fully describe the specific implementation process of the embodiment, another virtual machine-based virus notification method is provided, as shown in fig. 2, the method includes:
step 201, acquiring behavior characteristics corresponding to a plurality of virus samples;
step 202, determining a virus reporting monitoring point and a virus reporting experience value of the virus reporting monitoring point according to the behavior characteristics corresponding to the plurality of virus samples.
In step 201 and step 202, before virus program detection is performed, which positions in the virtual machine are to be monitored are determined, specifically, a large number of virus samples are analyzed, wherein a virus sample is an executable program containing a virus, behavior characteristics of the virus sample are extracted, the behavior characteristics may include functions called by the virus sample in an execution process and a sequence of calling functions, then the behavior characteristics of the virus sample are summarized, general behavior characteristics of the virus sample are extracted, characteristics with large differences between the virus sample and a security program are summarized, so that calling functions corresponding to the characteristics are determined according to the general behavior characteristics of the virus sample and the characteristics with large differences from the security program, the calling functions are virus reporting monitoring points, and the executable program suspected to contain the virus can be quickly locked through monitoring the virus reporting monitoring points, in addition, the importance degree of each monitoring point, namely the virus reporting experience value, is determined according to the general behavior characteristics of the virus sample and the safety program with larger difference, so that the behavior characteristics of the target program are quantified, and the virus program is locked by monitoring the virus reporting monitoring points more accurately.
The step 202 specifically includes:
2021, analyzing the virus reporting key behavior characteristics of the plurality of virus samples and the key weight of the virus reporting key behavior characteristics according to the behavior characteristics corresponding to the plurality of virus samples and the preset safety program behavior characteristics;
step 2022, determining a call function corresponding to the key behavior feature of the virus reporting as a virus reporting monitoring point, and determining the key weight of the key behavior feature of the virus reporting as a virus reporting experience value of the virus reporting monitoring point.
In step 2021 and step 2022, by analyzing and summarizing the behavior characteristics of a large number of virus samples and security samples, the general behavior characteristics of the virus samples and the behavior characteristics greatly different from the security samples are summarized, so that the behavior characteristics are used as the key behavior characteristics of virus detection, the structures related to the key behavior characteristics are used as virus reporting monitoring points, and statistical analysis is performed to quantify the importance degree of each key behavior characteristic, that is, the key weight of each virus reporting key behavior characteristic, so as to obtain the virus reporting experience value of each virus reporting monitoring point, thereby providing quantitative analysis rules for virus detection.
Step 203, executing the target program to be detected in the virtual machine;
step 204, monitoring at least one virus reporting monitoring point in the execution process of the target program, and recording the use condition of the at least one virus reporting monitoring point in the execution process of the target program;
step 205, calculating a virus detection value of the target program according to the use condition of the target program to the virus reporting monitoring points and the virus reporting experience value of each virus reporting monitoring point;
in step 206, if the virus detection value of the target program is greater than or equal to the preset virus empirical value, it is determined that the target program is a virus program.
Step 207, if the virus detection value of the target program is smaller than the preset virus empirical value, it is determined that the target program is not a virus program.
In the above steps 203 to 207, a quantitative detection method of the virus program is defined. Specifically, in step 203 and step 204, when the target program is executed in the virtual machine, the preset virus reporting monitoring points are monitored, and the calling condition of the target program to each virus reporting monitoring point in the virtual machine is recorded, where the virus reporting monitoring points may be stub functions in the virtual machine, and the use condition of each virus reporting monitoring point formed in the execution process of the target program is utilized to provide an analysis basis for virus detection.
Next, in step 205 to step 207, a virus detection value of the target program is calculated according to a pre-established virus reporting experience value corresponding to each virus reporting monitoring point, where the virus detection value of the target program may be a sum of virus reporting experience values corresponding to each virus reporting monitoring point used by the target program, for example, the target program calls the virus reporting monitoring point A, B, C, D, the virus reporting experience values of the virus reporting monitoring point A, B, C, D are 1, 2, and 3, respectively, and then the virus reporting detection value of the target program is 1+1+2+3 ═ 7. And then judging the relation between the virus reporting empirical value of the target program and a preset virus empirical value to determine whether the target program is a virus program, wherein the preset virus empirical value is obtained by analyzing a large number of virus samples and safety samples, and the preset virus empirical value is used as a partition to maximally distinguish the virus reporting empirical value of the virus sample from the virus reporting empirical value of the safety sample. For example, if the preset virus experience value is 5, if the preset virus experience value is greater than or equal to 5, the target program is determined to be a virus program, and if the preset virus experience value is less than 5, the target program is not a virus program, and in the example of the target program, the target program may be considered to be a virus program.
After determining that the target program is a virus program, step 208, the target program is added to a virus program library.
Step 209, when the number of the virus programs in the virus program library exceeds a preset number threshold, acquiring behavior characteristics corresponding to the virus programs in the virus program library, and updating the virus reporting monitoring points and the virus reporting experience values of the virus reporting monitoring points according to the behavior characteristics.
In step 208 and step 209, in order to improve the accuracy of judging the virus program, it is necessary to continuously correct the virus reporting experience values of the virus reporting monitoring points and the virus reporting verification points and the preset virus experience values, specifically, a target program determined as a virus program may be used as a virus sample, and a target program determined as a safety program may be used as a safety sample, and the virus reporting experience values of the virus reporting monitoring points and the virus reporting monitoring points, and even the preset virus experience values, are continuously updated and corrected by using the methods in step 201 and step 202, so that the method is more suitable for detecting a continuously changing virus.
It should be noted that, by detecting the virus reporting monitoring points, the present application may also detect a virus program by using a calling feature of the target program to each of the virus reporting monitoring points, and the second virus detection method provided in the embodiment of the present application may specifically include:
step A1, acquiring a preset execution characteristic list, wherein the preset execution characteristic list comprises a preset execution characteristic blacklist;
step A2, determining the execution characteristics of the target program according to the use condition of the target program on the virus reporting monitoring point, and inquiring whether the execution characteristics of the target program belong to malicious execution characteristics contained in a preset execution characteristic blacklist;
step a3, if the execution characteristic of the target program belongs to the malicious execution characteristic, determining that the target program contains a virus.
Step A4, if the execution characteristics of the target program do not belong to the malicious execution characteristics, querying whether the execution characteristics of the target program belong to the safe execution characteristics contained in the preset execution characteristic white list;
step a5, if the execution characteristic of the target program belongs to the safe execution characteristic, determining that the target program does not contain virus.
Step a6, if the execution characteristics of the target program do not belong to the security execution characteristics, the target program is marked as a suspicious program, and the execution characteristics corresponding to the suspicious program are reported to the virus management system, so as to analyze whether the suspicious program contains viruses or not by using the virus management system.
In the above steps a1 to a6, whether the target program is infected is determined by using a preset execution feature list, where the preset execution feature list includes a black list and a white list, the black list stores malicious execution features, which are presented when the virus program is called, in advance, and the white list stores security execution features, which are presented when the security program is called, in advance. And if the execution characteristics of the target program do not hit the blacklist or the white list, the program is judged to be a suspicious program, and the suspicious program is reported to a virus management system to further judge the program, wherein the virus management system can be specifically an expert system.
In addition, if the target program is a suspicious program, the malicious program management system can be reported, so that whether the target program is infected or not is judged by the malicious program management system, and the virus reporting monitoring point, the virus reporting experience value of the virus reporting verification point and the preset virus experience value are corrected according to the judgment result of the malicious program management system, so that the accuracy and the efficiency of virus detection are improved.
Further, as a specific implementation of the method in fig. 1, an embodiment of the present application provides a virus reporting apparatus based on a virtual machine, and as shown in fig. 3, the apparatus includes: target program execution module 31, monitoring module 32, virus detection module 33.
An object program execution module 31, configured to execute an object program to be detected in a virtual machine;
the monitoring module 32 is configured to monitor at least one virus reporting monitoring point during the execution process of the target program, and record a use condition of the at least one virus reporting monitoring point during the execution process of the target program;
and the virus detection module 33 is configured to determine whether the target program is a virus program according to the use condition of the target program to the virus reporting monitoring point.
In a specific application scenario, as shown in fig. 4, the virus detection module 33 specifically includes: detection value calculation section 331 and virus program detection section 332.
The detection value calculation unit 331 is configured to calculate a virus detection value of the target program according to a usage situation of the virus reporting monitoring points by the target program and a virus reporting experience value of each virus reporting monitoring point;
the virus program detecting unit 332 is configured to determine that the target program is a virus program if the virus detection value of the target program is greater than or equal to the preset virus empirical value.
In a specific application scenario, as shown in fig. 4, the virus detection module 33 further includes: a security program detecting unit 333.
And the safety program detection unit 333 is configured to determine that the target program is not a virus program if the virus detection value of the target program is smaller than a preset virus empirical value.
In a specific application scenario, as shown in fig. 4, the apparatus further includes: a behavior characteristic obtaining module 34 and a monitoring point determining module 35.
A behavior feature obtaining module 34, configured to obtain behavior features corresponding to multiple virus samples before executing a target program to be detected in a virtual machine;
and the monitoring point determining module 35 is configured to determine a virus reporting monitoring point and a virus reporting experience value of the virus reporting monitoring point according to behavior characteristics corresponding to the plurality of virus samples.
In a specific application scenario, as shown in fig. 4, the monitoring point determining module 35 specifically includes: a weight determination unit 351 and an empirical value determination unit 352.
The weight determining unit 351 is configured to analyze the virus reporting key behavior characteristics of the multiple virus samples and the key weights of the virus reporting key behavior characteristics according to the behavior characteristics corresponding to the multiple virus samples and the preset security program behavior characteristics;
the empirical value determining unit 352 is configured to determine a call function corresponding to the toxicity reporting key behavior feature as a toxicity reporting monitoring point, and determine a key weight of the toxicity reporting key behavior feature as an toxicity reporting empirical value of the toxicity reporting monitoring point.
In a specific application scenario, as shown in fig. 4, the apparatus further includes: a virus library creation module 36.
And a virus library establishing module 36, configured to add the target program into the virus library after determining that the target program is a virus program.
In a specific application scenario, as shown in fig. 4, the apparatus further includes: a monitoring point update module 37.
And the monitoring point updating module 37 is configured to, when the number of the virus programs in the virus program library exceeds a preset number threshold, obtain behavior characteristics corresponding to the virus programs in the virus program library, and update the virus reporting monitoring points and the virus reporting experience values of the virus reporting monitoring points according to the behavior characteristics.
It should be noted that, the virus reporting device based on the virtual machine in the embodiment of the present application is further configured to:
step A1, acquiring a preset execution characteristic list, wherein the preset execution characteristic list comprises a preset execution characteristic blacklist;
step A2, determining the execution characteristics of the target program according to the use condition of the target program on the virus reporting monitoring point, and inquiring whether the execution characteristics of the target program belong to malicious execution characteristics contained in a preset execution characteristic blacklist;
step a3, if the execution characteristic of the target program belongs to the malicious execution characteristic, determining that the target program contains a virus.
Step A4, if the execution characteristics of the target program do not belong to the malicious execution characteristics, querying whether the execution characteristics of the target program belong to the safe execution characteristics contained in the preset execution characteristic white list;
step a5, if the execution characteristic of the target program belongs to the safe execution characteristic, determining that the target program does not contain virus.
Step a6, if the execution characteristics of the target program do not belong to the security execution characteristics, the target program is marked as a suspicious program, and the execution characteristics corresponding to the suspicious program are reported to the virus management system, so as to analyze whether the suspicious program contains viruses or not by using the virus management system.
In the above steps a1 to a6, whether the target program is infected is determined by using a preset execution feature list, where the preset execution feature list includes a black list and a white list, the black list stores malicious execution features, which are presented when the virus program is called, in advance, and the white list stores security execution features, which are presented when the security program is called, in advance. And if the execution characteristics of the target program do not hit the blacklist or the white list, the program is judged to be a suspicious program, and the suspicious program is reported to a virus management system to further judge the program, wherein the virus management system can be specifically an expert system.
In addition, if the target program is a suspicious program, the malicious program management system can be reported, so that whether the target program is infected or not is judged by the malicious program management system, and the virus reporting monitoring point, the virus reporting experience value of the virus reporting verification point and the preset virus experience value are corrected according to the judgment result of the malicious program management system, so that the accuracy and the efficiency of virus detection are improved.
It should be noted that other corresponding descriptions of the functional units related to the virus reporting device based on the virtual machine provided in the embodiment of the present application may refer to the corresponding descriptions in fig. 1 and fig. 2, and are not described herein again.
Based on the methods shown in fig. 1 and fig. 2, correspondingly, the present application further provides a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the virtual machine-based virus notification method shown in fig. 1 and fig. 2 is implemented.
Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.), and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the implementation scenarios of the present application.
Based on the method shown in fig. 1 and fig. 2 and the virtual device embodiment shown in fig. 3 and fig. 4, in order to achieve the above object, an embodiment of the present application further provides a computer device, which may specifically be a personal computer, a server, a network device, and the like, where the computer device includes a storage medium and a processor; a storage medium for storing a computer program; a processor for executing a computer program to implement the virtual machine based virus notification method as described above with reference to fig. 1 and 2.
Optionally, the computer device may also include a user interface, a network interface, a camera, Radio Frequency (RF) circuitry, sensors, audio circuitry, a WI-FI module, and so forth. The user interface may include a Display screen (Display), an input unit such as a keypad (Keyboard), etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (e.g., a bluetooth interface, WI-FI interface), etc.
It will be appreciated by those skilled in the art that the present embodiment provides a computer device architecture that is not limiting of the computer device, and that may include more or fewer components, or some components in combination, or a different arrangement of components.
The storage medium may further include an operating system and a network communication module. An operating system is a program that manages and maintains the hardware and software resources of a computer device, supporting the operation of information handling programs, as well as other software and/or programs. The network communication module is used for realizing communication among components in the storage medium and other hardware and software in the entity device.
Through the description of the above embodiment, those skilled in the art can clearly understand that the present application can be implemented by software plus a necessary general hardware platform, and also can be implemented by hardware, where the usage of the virus reporting monitoring point by the target program that needs to be virus-detected in the execution process is recorded by using a virtual machine technology, and then a heuristic virus check and kill is performed on the usage of the virus reporting monitoring point according to the extracted target program to detect whether the target program is a virus program. The method and the system utilize the virtual machine technology, not only can effectively obtain the running record of the target program when the target program is executed in the virtual machine, but also can not influence the real computer environment to protect the safety of the computer, and simultaneously, heuristic virus detection is carried out based on the running record of the target program, so that the method and the system are helpful for improving the detection rate of unknown viruses such as novel viruses and variant viruses.
Those skilled in the art will appreciate that the figures are merely schematic representations of one preferred implementation scenario and that the blocks or flow diagrams in the figures are not necessarily required to practice the present application. Those skilled in the art will appreciate that the modules in the devices in the implementation scenario may be distributed in the devices in the implementation scenario according to the description of the implementation scenario, or may be located in one or more devices different from the present implementation scenario with corresponding changes. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The above application serial numbers are for description purposes only and do not represent the superiority or inferiority of the implementation scenarios. The above disclosure is only a few specific implementation scenarios of the present application, but the present application is not limited thereto, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present application.