CN112733141B - Information processing method and device - Google Patents
Information processing method and device Download PDFInfo
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- CN112733141B CN112733141B CN202011631748.3A CN202011631748A CN112733141B CN 112733141 B CN112733141 B CN 112733141B CN 202011631748 A CN202011631748 A CN 202011631748A CN 112733141 B CN112733141 B CN 112733141B
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
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Abstract
The application discloses an information processing method and device. In the method, a target keyword set for detecting the simulator is obtained, wherein the target keyword set is obtained according to candidate keywords detected in a plurality of preset simulators in a candidate keyword set, and the candidate keyword set comprises a plurality of keywords related to the simulator, which are collected in advance. And detecting the target keywords in the target keyword set at the specific storage position of the object to be detected, and determining the object to be detected as the simulator under the condition that the target keywords in the target keyword set are detected at the specific storage position of the object to be detected. According to the method and the device, the target keywords in the target keyword set can not be detected at other positions except the specific storage position of the object to be detected, so that the detection range of the target keywords is reduced, the time can be saved, and the detection efficiency can be improved under the condition that the detection accuracy is ensured.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to an information processing method and apparatus.
Background
With the rapid development of the technology, an android simulator (which simulates an android operating system on a computer and can install, use and uninstall software of an android application program, that is, can operate the android system on the computer) has been widely used in the society.
However, due to the open source nature of the android operating system, more and more lawless persons forge the running environment through the android system simulator to run the application program, and then perform malicious batch billing or malicious destruction based on the application program.
Therefore, the operating environment of the application program needs to be detected, and whether the application program operates in the android simulator is known in time, and a corresponding policy is issued.
Disclosure of Invention
The application discloses an information processing method and device.
In a first aspect, the present application shows an information processing method, comprising:
acquiring a target keyword set for detecting a simulator, wherein the target keyword set is acquired according to candidate keywords detected in a plurality of preset simulators in a candidate keyword set, and the candidate keyword set comprises a plurality of keywords related to the simulator which are collected in advance;
detecting a target keyword in the target keyword set at a specific storage position of an object to be detected, wherein the specific storage position is obtained according to storage positions for respectively storing the detected candidate keywords in each preset simulator;
and determining the object to be detected as a simulator under the condition that the target keywords in the target keyword set are detected at the specific storage position of the object to be detected.
In an optional implementation, the method further includes:
detecting any one candidate keyword detected in the plurality of preset simulators in the candidate keyword set on a plurality of real object machines respectively;
counting a first number of real physical machines in which the candidate keyword is detected, among the plurality of real physical machines;
under the condition that the first number is larger than the preset number, the candidate keywords are removed from the candidate keyword set;
and acquiring the target keyword set according to the candidate keywords detected in the plurality of preset simulators in the candidate keyword set after the elimination.
In an optional implementation, the method further includes:
counting a second number of the target keywords detected at the specific storage position of the object to be detected respectively under the condition that the target keywords in the target keyword set are detected at the specific storage position of the object to be detected, and acquiring the weight of each target keyword detected at the specific storage position of the object to be detected;
obtaining a simulator evaluation score of the object to be detected according to the second quantity and the weight;
and under the condition that the evaluation score of the simulator is larger than a preset threshold value, executing the step of determining the object to be detected as the simulator.
In an optional implementation manner, the obtaining a simulator rating score of the object to be detected according to the second quantity and the weight includes:
for any target keyword detected at the specific storage position of the object to be detected, acquiring a keyword score of the target keyword according to the second number of the target keyword detected at the specific storage position of the object to be detected and the weight of the target keyword;
and obtaining the evaluation score of the simulator according to the keyword scores of the target keywords detected at the specific storage position of the object to be detected.
In an optional implementation, the method further includes:
for any candidate keyword detected in the plurality of preset simulators in the candidate keyword set, obtaining a third number of the candidate keywords detected in the plurality of preset simulators;
acquiring the weight of the candidate keywords according to the third number of the candidate keywords detected in the plurality of preset simulators;
and forming a corresponding table entry by the candidate keywords and the weights of the candidate keywords, and storing the corresponding table entry in the corresponding relation between the keywords and the weights.
In an optional implementation manner, the obtaining the weight of each target keyword detected at the specific storage location includes:
and searching weights respectively corresponding to all target keywords detected at a specific storage position of the object to be detected in the corresponding relation between the keywords and the weights.
In an optional implementation, the method further includes:
and under the condition that the object to be detected is determined to be the simulator, updating the weights respectively corresponding to the target keywords respectively detected at the specific storage position of the object to be detected in the corresponding relation according to the second quantity of the target keywords respectively detected at the specific storage position of the object to be detected.
In an optional implementation, the method further includes:
under the condition that the object to be detected is determined to be a simulator, detecting the target keywords in the target keyword set at the positions of the object to be detected except the specific storage position;
when the target keywords in the target keyword set are detected at positions of the object to be detected except a specific storage position, adding: a location of the target keyword other than the particular storage location is detected.
In a second aspect, the present application shows an information processing apparatus comprising;
the simulator comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a target keyword set for detecting a simulator, the target keyword set is acquired according to candidate keywords detected in a plurality of preset simulators in a candidate keyword set, and the candidate keyword set comprises a plurality of keywords related to the simulator, which are collected in advance;
the first detection module is used for detecting the target keywords in the target keyword set at a specific storage position of an object to be detected, wherein the specific storage position is obtained according to the storage positions of the detected candidate keywords respectively stored in the preset simulators;
and the determining module is used for determining the object to be detected as the simulator under the condition that the target keywords in the target keyword set are detected at the specific storage position of the object to be detected.
In an optional implementation, the apparatus further comprises:
a second detection module, configured to detect, on a plurality of real object machines, a candidate keyword for any one of the candidate keywords detected in the plurality of preset simulators in the candidate keyword set, respectively;
the first statistical module is used for counting a first number of real physical machines of the candidate keywords in the plurality of real object machines;
the removing module is used for removing the candidate keywords from the candidate keyword set under the condition that the first number is larger than the preset number;
and the second acquisition module is used for acquiring the target keyword set according to the candidate keywords detected in the plurality of preset simulators in the candidate keyword set after being removed.
In an optional implementation, the apparatus further comprises:
a second counting module, configured to count a second number of target keywords detected at the specific storage location of the object to be detected respectively when the target keywords in the target keyword set are detected at the specific storage location of the object to be detected, and a third obtaining module, configured to obtain weights of the target keywords detected at the specific storage location of the object to be detected;
a fourth obtaining module, configured to obtain a simulator rating score of the object to be detected according to the second quantity and the weight;
the determination module is further to: and determining the object to be detected as the simulator under the condition that the evaluation value of the simulator is greater than a preset threshold value.
In an optional implementation manner, the fourth obtaining module includes:
a first obtaining unit, configured to, for any one target keyword detected at a specific storage location of the object to be detected, obtain a keyword score of the target keyword according to a second number of the target keyword detected at the specific storage location of the object to be detected and a weight of the target keyword;
and the second acquisition unit is used for acquiring the evaluation score of the simulator according to the keyword scores of the target keywords detected at the specific storage position of the object to be detected.
In an optional implementation manner, the apparatus further includes:
a fifth obtaining module, configured to obtain, for any one candidate keyword detected in the plurality of preset simulators in the candidate keyword set, a third number of the candidate keywords detected in the plurality of preset simulators;
a sixth obtaining module, configured to obtain a weight of the candidate keyword according to a third number of the candidate keywords detected in the multiple preset simulators;
and the storage module is used for forming a corresponding table entry by the candidate keywords and the weights of the candidate keywords and storing the corresponding table entry in the corresponding relation between the keywords and the weights.
In an optional implementation manner, the second obtaining module is specifically configured to: and searching weights respectively corresponding to all target keywords detected at a specific storage position of the object to be detected in the corresponding relation between the keywords and the weights.
In an optional implementation, the apparatus further comprises:
and the updating module is used for updating the weights respectively corresponding to the target keywords respectively detected at the specific storage position of the object to be detected in the corresponding relation according to the second quantity of the target keywords respectively detected at the specific storage position of the object to be detected under the condition that the object to be detected is determined to be the simulator.
In an optional implementation, the apparatus further comprises:
the third detection module is used for detecting the target keywords in the target keyword set at the positions of the object to be detected except the specific storage position under the condition that the object to be detected is determined to be a simulator;
an adding module, configured to add, in a specific storage location, when a target keyword in the target keyword set is detected in a location of the object to be detected other than the specific storage location: a location of the target keyword other than the particular storage location is detected.
In a third aspect, the present application shows an electronic device comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the information processing method according to the first aspect.
In a fourth aspect, the present application shows a non-transitory computer-readable storage medium having instructions which, when executed by a processor of an electronic device, enable the electronic device to perform the information processing method according to the first aspect.
In a fifth aspect, the present application shows a computer program product, in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform the information processing method according to the first aspect.
The technical scheme provided by the application can comprise the following beneficial effects:
in the method, a target keyword set for detecting the simulator is obtained, wherein the target keyword set is obtained according to candidate keywords detected in a plurality of preset simulators in a candidate keyword set, and the candidate keyword set comprises a plurality of keywords related to the simulator, which are collected in advance. And detecting the target keywords in the target keyword set at the specific storage position of the object to be detected, and determining the object to be detected as the simulator under the condition that the target keywords in the target keyword set are detected at the specific storage position of the object to be detected.
The target keyword set is acquired according to the candidate keywords detected in the multiple preset simulators in the candidate keyword set, and the specific storage position is acquired according to the storage positions in the preset simulators, where the "detected candidate keywords" are respectively stored, so that the target keywords in the target keyword set are often stored in the specific storage positions of the simulators, and are rarely stored in other positions of the simulators except the specific storage positions.
In addition, whether the object to be detected is a simulator or not is detected by detecting the target keywords in the target keyword set at the specific storage position of the object to be detected, the method focuses on the inherent characteristics of the object to be detected in principle, and does not depend on the application program running on the object to be detected, so that the decoupling of the detection mode and the application program running on the object to be detected can be realized, the coupling degree is reduced, and the detection logic is simplified.
And secondly, the method does not depend on tools with complex logics such as algorithms and models, and reduces the detection complexity.
And the candidate keyword set can determine the detection accuracy of the detection mode of the application, and when a technician collects candidate keywords in advance to form the candidate keyword set, the detection accuracy of the detection mode of the application can be improved as long as the technician can collect a large number of candidate keywords with high coverage. Therefore, the target keyword set can be updated according to the characteristics of a new simulator on the market after the online detection, so that the timeliness of the target keyword set is matched with the timeliness of the existing simulator on the market, and the high detection accuracy can be kept by the method.
Drawings
Fig. 1 is a flowchart of the steps of an information processing method of the present application.
FIG. 2 is a flow chart of steps of an information processing method of the present application.
Fig. 3 is a block diagram of a configuration of an information processing apparatus according to the present application.
Fig. 4 is a block diagram of an electronic device shown in the present application.
Fig. 5 is a block diagram of an electronic device shown in the present application.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.
In general, names of simulators may be stored in the simulators, so in one mode, the names of the simulators may be searched in advance to form a name set, then when detecting whether the running environment of the application program is a simulator, names in the name set may be searched in all storage locations in the running environment in a traversal manner, and if names in the name set are searched in the running environment, it is stated that the names of the simulators are stored in the running environment, so that it may be determined that the running environment of the application program is a simulator.
However, in the above manner, performing the traversal search in all the storage locations in the execution environment may result in a time consuming search process, which may reduce the efficiency of detecting whether the execution environment of the application is the simulator.
Therefore, in order to improve the efficiency of detecting the running environment of the application, referring to fig. 1, a flowchart of steps of an information processing method of the present application is shown, where the method is applied to an electronic device, and the method may specifically include the following steps:
in step S101, a target keyword set for detecting a simulator is obtained, where the target keyword set is obtained according to candidate keywords detected in a plurality of preset simulators in a candidate keyword set, and the candidate keyword set includes a plurality of keywords related to a simulator collected in advance.
In the present application, the target keyword set for detecting the simulator may be set in advance, and thus, the present application may directly obtain the set of target keywords set in advance.
The process of setting the target keyword set in advance may include:
1011. a candidate keyword set is obtained, and the candidate keyword set comprises a plurality of keywords related to a simulator collected in advance.
The candidate keywords in the candidate keyword set may be keywords that may appear in the simulator and the like that are counted by technicians according to experience in advance, and a large number of keywords may be obtained through statistics and used as keywords related to the simulator.
For example, keywords that may appear in a large number of different kinds of simulators may be gathered for the underlying principles of the simulators, common features of different vendors 'simulators, respectively different features of different vendors' simulators, and used as simulator related keywords.
The principles of the current simulator may include: based on the principle that an android X86 system is used as a kernel and a VBox virtual machine is used as a container, technical personnel can mine keywords related to the principle of the simulator. For example, X86, VBox, inter, AMD, nox, tbox, and Mumu, etc. may be included, and of course, other keywords may be included, which is not exemplified here.
1012. And respectively detecting each candidate keyword in the candidate keyword set in a plurality of preset simulators.
A plurality of simulators may be provided in advance, and the plurality of simulators may include simulators of different manufacturers (brands), simulators of different principles, and the like, to improve coverage.
For any one of the preset simulators, each candidate keyword in the candidate keyword set may be detected in the preset simulator, specifically, full-system scanning may be performed, for example, each candidate keyword in the candidate keyword set may be detected in all storage locations of a hardware layer and all storage locations of a software layer of the preset simulator, so as to improve a coverage.
Specifically, each candidate keyword in the candidate keyword set and the like may be respectively detected in a file of an I/O device of the preset simulator, a file of a driver, a file of a sensor, a file of a camera, a file of a microphone, a file of a screen, a file of a gyroscope, a system control file of the simulator, information of a process and information of a port.
The same is true for each of the other ones of the plurality of preset simulators.
1013. And acquiring a target keyword set according to the candidate keywords detected in the plurality of preset simulators in the candidate keyword set.
For example, in one embodiment, the candidate keywords detected in the plurality of preset simulators in the candidate keyword set may be combined into the target keyword set.
In step S102, a target keyword in the target keyword set is detected at a specific storage location of the object to be detected, where the specific storage location is obtained according to storage locations where the detected candidate keywords are respectively stored in each preset simulator.
The object to be detected may include an execution environment of the application program and the like, and the execution environment of the application program includes a real physical machine or a simulator installed on the physical machine for simulating the real physical machine and the like.
The specific storage locations include: a particular memory directory of the system, etc., e.g., "operating system/cpu info", etc.
After detecting each candidate keyword in the candidate keyword set in each of the plurality of preset simulators in step S101, a storage location in each preset simulator where the candidate keyword in the candidate keyword set is stored may be obtained and used as a specific storage location, and then the specific storage location is configured on the electronic device.
In this way, in this step, a specific storage location configured in advance may be obtained, and then, for any one target keyword in the target keyword set, the target keyword may be detected at the specific storage location of the object to be detected, and the detection result may include two types: one is that the target keyword is stored in the specific storage position of the object to be detected, and the other is that the target keyword is not stored in the specific storage position of the object to be detected. The same is true for each of the other target keywords in the set of target keywords.
In step S103, it is determined whether a target keyword in the target keyword set is detected at a specific storage location of the object to be detected.
In the case that the target keyword in the target keyword set is detected at the specific storage location of the object to be detected, in step S104, it is determined that the object to be detected is a simulator.
In the case that the target keyword in the target keyword set is not detected in the specific storage location of the object to be detected, in step S105, it is determined that the object to be detected is a real physical machine or the like.
In the method, a target keyword set for detecting the simulator is obtained, wherein the target keyword set is obtained according to candidate keywords detected in a plurality of preset simulators in a candidate keyword set, and the candidate keyword set comprises a plurality of keywords related to the simulator, which are collected in advance. And detecting the target keywords in the target keyword set at the specific storage position of the object to be detected, and determining the object to be detected as the simulator under the condition that the target keywords in the target keyword set are detected at the specific storage position of the object to be detected.
The target keyword set is acquired according to the candidate keywords detected in the multiple preset simulators in the candidate keyword set, and the specific storage position is acquired according to the storage positions in the preset simulators, where the "detected candidate keywords" are respectively stored, so that the target keywords in the target keyword set are often stored in the specific storage positions of the simulators, and are rarely stored in other positions of the simulators except the specific storage positions.
In addition, whether the object to be detected is a simulator or not is detected by detecting the target keywords in the target keyword set at the specific storage position of the object to be detected, the method focuses on the inherent characteristics of the object to be detected in principle, and does not depend on the application program running on the object to be detected, so that the decoupling of the detection mode and the application program running on the object to be detected can be realized, the coupling degree is reduced, and the detection logic is simplified.
And secondly, the method does not depend on tools with complex logics such as algorithms and models, and reduces the detection complexity.
And the candidate keyword set can determine the detection accuracy of the detection mode of the application, and when a technician collects candidate keywords in advance to form the candidate keyword set, the detection accuracy of the detection mode of the application can be improved as long as the technician can collect a large number of candidate keywords with high coverage. Therefore, the target keyword set can be updated according to the characteristics of a new simulator on the market after the online detection, so that the timeliness of the target keyword set is matched with the timeliness of the existing simulator on the market, and the high detection accuracy can be kept by the method.
In an embodiment of the application, since the target keywords are obtained according to keywords related to the simulator, the target keywords can reflect characteristics of the simulator, and thus, as long as one target keyword in the target keyword set is stored in the specific storage location, it is indicated that the object to be detected has characteristics of the simulator, and the object to be detected can often be determined to be the simulator.
Sometimes, however, in one possible scenario, a particular storage location on the real physical machine may also store at least one target keyword from the set of target keywords,
in this case, in the manner shown in fig. 1, at least one target keyword in the target keyword set may be detected at a specific storage location in the real physical machine, so that the real physical machine may be erroneously determined as a simulator, resulting in an erroneous determination.
Therefore, in order to avoid the occurrence of misjudgment, in another embodiment of the present invention, in step 1013 of step S101, when the target keyword set is acquired from the candidate keywords detected in the plurality of preset simulators in the candidate keyword set, the following processes 11) to 14) may be performed for any one candidate keyword detected in the plurality of preset simulators in the candidate keyword set, and the same is true for each of the other candidate keywords detected in the plurality of preset simulators in the candidate keyword set.
The specific process comprises the following steps:
11 Respectively, the candidate keyword is detected on a plurality of real object machines.
12 And) counting a first number of real physical devices in which the candidate keyword is detected among the plurality of real physical devices.
13 And if the first number is larger than the preset number, eliminating the candidate keyword from the candidate keyword set.
The preset number may include 10, 50, 100, 200, etc., and may be determined according to practical situations, and the present application does not limit the specific numerical value of the preset number.
14 And) obtaining a target keyword set according to the candidate keywords detected in the plurality of preset simulators in the candidate keyword set after the elimination.
For example, in one embodiment, the candidate keywords detected in the plurality of preset simulators in the rejected candidate keyword set may be combined into the target keyword set.
If the candidate keyword is stored in the real physical machines with the number more than the preset number, the candidate keyword is also the characteristics of the real physical machines with the considerable number, so that the situation of misjudgment is easily caused when whether the object to be detected is the simulator or not is detected according to the candidate keyword according to the thought of the figure 1, therefore, the candidate keyword can be removed from the candidate keyword set, the target keyword set is obtained according to the removed candidate keyword set, the situation that whether the object to be detected is the simulator or not is no longer detected according to the candidate keyword according to the thought of the figure 1, and the situation of misjudgment can be avoided as much as possible.
In the foregoing embodiment, in the case that the target keyword in the target keyword set is detected at the specific storage location of the object to be detected, step S104 is executed: and determining the object to be detected as a simulator.
For example, as long as one target keyword in the target keyword set is stored in the specific storage location, it indicates that the object to be detected has the characteristics of the simulator, and it may often be determined that the object to be detected is the simulator.
However, there may sometimes be a case, for example, where the number of target keywords stored in a particular storage location in the simulator is often large, and the target keywords may also be stored in a particular storage location on a real physical machine, but the number of target keywords stored is often small.
In this case, if it is the way according to the foregoing embodiment: as long as a target keyword in the target keyword set is stored in the specific storage location, it is determined that the object to be detected is the simulator, and thus, a situation that a real physical machine (a small number of target keywords, for example, 1 or 2 or the like, are stored in the specific storage location) is determined as the simulator, that is, a situation that a false judgment occurs may occur.
Therefore, in order to avoid the occurrence of the false determination, referring to fig. 2, the method further includes:
in the case that the target keywords in the target keyword set are detected at the specific storage location of the object to be detected, in step S201, a second number of the target keywords detected at the specific storage location of the object to be detected respectively is counted, and a weight of each of the target keywords detected at the specific storage location of the object to be detected is obtained.
Wherein, for any one target keyword detected in a specific storage location, the second number of the target keywords detected in the specific storage location can be counted, and the same is true for each other target keyword detected in the specific storage location.
In the present application, the number of occurrences of different target keywords in specific storage locations in a large number of simulators is not always the same, and the number of occurrences of different target keywords in specific storage locations in a large number of real physical machines is also often different.
Thus, different target keywords may contribute different degrees, i.e., weights, to the detection simulator.
For example, when the number of occurrences of a certain target keyword in a specific storage location in a large number of simulators is large, the probability that a certain object (e.g., an operating environment or the like) is a simulator is high if the target keyword is stored in the specific storage location in the object when determining whether the object is a simulator.
Accordingly, the smaller the number of occurrences of a certain target keyword in a specific storage location in a large number of simulators, the smaller the possibility that a certain object is a simulator if the target keyword is stored in the specific storage location in the object when determining whether the object is a simulator.
Therefore, when determining whether the object to be detected is a simulator, it is necessary to use the weights of the target keywords detected at the specific storage location of the object to be detected, in addition to the second number of the target keywords detected at the specific storage location of the object to be detected, respectively, so that the detection accuracy can be improved.
In the present application, after step 1012 "detecting a target keyword in the target keyword set at a specific storage location of an object to be detected" in step S101 is performed, for any one candidate keyword detected in a plurality of preset simulators in the candidate keyword set, a third number of the candidate keywords detected in the plurality of preset simulators is obtained. Then, the weight of the candidate keyword may be obtained according to the third number of the candidate keyword detected in the plurality of preset simulators, for example, the third number of the candidate keyword detected in the plurality of preset simulators may be used as the weight of the candidate keyword, or the weight of the candidate keyword may be obtained by multiplying the third number of the candidate keyword detected in the plurality of preset simulators by a specific coefficient. Then, the candidate keyword and the weight of the candidate keyword can be combined into a corresponding table entry, and the corresponding table entry is stored in the corresponding relation between the keyword and the weight.
In this way, when the weights of the target keywords detected at the specific storage location of the object to be detected are obtained, the weights corresponding to the target keywords detected at the specific storage location of the object to be detected can be searched in the corresponding relationship between the keywords and the weights.
In step S202, a simulator rating score of the object to be detected is obtained according to the second quantity and the weight.
This step can be realized by the following process, including:
2021. and for any target keyword detected at the specific storage position of the object to be detected, acquiring the keyword score of the target keyword according to the second quantity of the target keyword detected at the specific storage position of the object to be detected and the weight of the target keyword.
In one embodiment, a product between the second number of the detected target keywords at the specific storage location of the object to be detected and the weight of the target keywords may be calculated to obtain the keyword score of the target keywords.
The same is true for every other target keyword detected at a specific storage location of the object to be detected.
2022. And obtaining the evaluation score of the simulator according to the keyword scores of the target keywords detected at the specific storage position of the object to be detected.
In one approach, the keyword scores for each of the target keywords detected at a particular storage location may be summed to yield a simulator rating score.
In step S203, it is determined whether the simulator rating score is greater than a preset threshold.
The preset threshold may include 2, 5, or 8, etc., and the specific value of the preset threshold may be determined according to practical situations and will not be described in detail herein.
In the case that the simulator rating score is greater than the preset threshold, performing step S104: and determining the object to be detected as a simulator.
In the case where the simulator rating score is less than or equal to the preset threshold, step S105 is performed: and determining that the object to be detected is a real physical machine.
Further, in another embodiment of the present application, in a case that it is determined that the object to be detected is the simulator, the weights respectively corresponding to the target keywords detected at the specific storage location of the object to be detected may be updated in the correspondence between the keywords and the weights of the keywords according to the second number of the target keywords respectively detected at the specific storage location of the object to be detected. Therefore, the weight of the target keyword in the target keyword set is updated according to the real-time detection result of the object to be detected on line, so that the weight of the target keyword in the target keyword set can be closer to the actual condition, and the detection accuracy when other objects to be detected are detected to be simulators or not is improved.
In some cases, due to practical limitations, the preset simulator used in collecting the specific storage location in advance may not cover all the simulators on the market, but only part of the simulators on the market, so the specific storage location collected in advance described in step S102 may not be comprehensive, and may be omitted.
For example, the target keyword in the set of target keywords is not stored in a particular storage location in the missing simulator, but the target keyword is stored in a storage location other than the particular storage location in the missing simulator.
At this time, when a simulator similar to the missing simulator is detected based on the embodiment shown in fig. 1, a situation that the target keyword in the target keyword set is not detected in the specific storage location may occur, and then the simulator similar to the missing simulator may be determined as a real physical machine, resulting in a misjudgment situation.
Therefore, in order to avoid the occurrence of the erroneous judgment as much as possible, in another embodiment of the present application, in the case where the object to be detected is determined to be a simulator, the target keywords in the target keyword set are detected at a position other than the specific storage position of the object to be detected. In the case that the target keyword in the target keyword set is detected at a position of the object to be detected other than the specific storage position, then: a location other than the specific storage location of the target keyword is detected.
The dimension of the specific storage position is expanded, the detection dimension is increased on the specific storage position, the misjudgment condition is reduced as much as possible, and the detection accuracy is improved.
It is noted that for simplicity of description, the method embodiments are shown as a series of acts or combinations, but those skilled in the art will recognize that the present application is not limited by the order of acts, as some steps may, in accordance with the present application, occur in other orders or concurrently. Further, those of skill in the art will also appreciate that the embodiments described in the specification are exemplary of alternative embodiments and that the acts involved are not necessarily required of the application.
Referring to fig. 3, a block diagram of an information processing apparatus according to the present application is shown, and the apparatus may specifically include the following modules:
a first obtaining module 11, configured to obtain a target keyword set for detecting a simulator, where the target keyword set is obtained according to candidate keywords detected in multiple preset simulators in a candidate keyword set, and the candidate keyword set includes multiple keywords related to the simulator collected in advance;
the first detection module 12 is configured to detect a target keyword in the target keyword set at a specific storage location of an object to be detected, where the specific storage location is obtained according to storage locations where the detected candidate keywords are respectively stored in each preset simulator;
the determining module 13 is configured to determine that the object to be detected is a simulator when a target keyword in the target keyword set is detected at a specific storage location of the object to be detected.
In an optional implementation, the apparatus further comprises:
a second detection module, configured to detect, on a plurality of real object machines, a candidate keyword for any one of the candidate keywords detected in the plurality of preset simulators in the candidate keyword set, respectively;
the first statistical module is used for counting a first number of real physical machines of the candidate keywords in the plurality of real object machines;
the removing module is used for removing the candidate keywords from the candidate keyword set under the condition that the first number is larger than the preset number;
and the second acquisition module is used for acquiring the target keyword set according to the candidate keywords detected in the plurality of preset simulators in the candidate keyword set after being removed.
In an optional implementation manner, the apparatus further includes:
a second counting module, configured to count a second number of target keywords detected at the specific storage location of the object to be detected respectively when the target keywords in the target keyword set are detected at the specific storage location of the object to be detected, and a third obtaining module, configured to obtain weights of the target keywords detected at the specific storage location of the object to be detected;
a fourth obtaining module, configured to obtain a simulator rating score of the object to be detected according to the second quantity and the weight;
the determination module is further to: and determining the object to be detected as the simulator under the condition that the evaluation value of the simulator is greater than a preset threshold value.
In an optional implementation manner, the fourth obtaining module includes:
a first obtaining unit, configured to, for any one target keyword detected at a specific storage location of the object to be detected, obtain a keyword score of the target keyword according to a second number of the target keyword detected at the specific storage location of the object to be detected and a weight of the target keyword;
and the second acquisition unit is used for acquiring the evaluation score of the simulator according to the keyword scores of the target keywords detected at the specific storage position of the object to be detected.
In an optional implementation, the apparatus further comprises:
a fifth obtaining module, configured to obtain, for any one candidate keyword detected in the plurality of preset simulators in the candidate keyword set, a third number of the candidate keywords detected in the plurality of preset simulators;
a sixth obtaining module, configured to obtain a weight of the candidate keyword according to a third number of the candidate keywords detected in the plurality of preset simulators;
and the storage module is used for forming a corresponding table entry by the candidate keywords and the weights of the candidate keywords and storing the corresponding table entry in the corresponding relation between the keywords and the weights.
In an optional implementation manner, the second obtaining module is specifically configured to: and searching weights respectively corresponding to all target keywords detected at a specific storage position of the object to be detected in the corresponding relation between the keywords and the weights.
In an optional implementation, the apparatus further comprises:
and the updating module is used for updating the weights respectively corresponding to the target keywords respectively detected at the specific storage position of the object to be detected in the corresponding relation according to the second quantity of the target keywords respectively detected at the specific storage position of the object to be detected under the condition that the object to be detected is determined to be the simulator.
In an optional implementation, the apparatus further comprises:
the third detection module is used for detecting the target keywords in the target keyword set at the positions of the object to be detected except the specific storage position under the condition that the object to be detected is determined to be a simulator;
an adding module, configured to add, in a specific storage location, when a target keyword in the target keyword set is detected in a location of the object to be detected other than the specific storage location: a location of the target keyword other than the particular storage location is detected.
In the method, a target keyword set for detecting the simulator is obtained, wherein the target keyword set is obtained according to candidate keywords detected in a plurality of preset simulators in a candidate keyword set, and the candidate keyword set comprises a plurality of keywords related to the simulator, which are collected in advance. And detecting the target keywords in the target keyword set at the specific storage position of the object to be detected, and determining the object to be detected as the simulator under the condition that the target keywords in the target keyword set are detected at the specific storage position of the object to be detected.
The target keyword set is acquired according to the candidate keywords detected in the multiple preset simulators in the candidate keyword set, and the specific storage position is acquired according to the storage positions in the preset simulators, where the "detected candidate keywords" are respectively stored, so that the target keywords in the target keyword set are often stored in the specific storage positions of the simulators, and are rarely stored in other positions of the simulators except the specific storage positions.
In addition, whether the object to be detected is a simulator or not is detected by detecting the target keywords in the target keyword set at the specific storage position of the object to be detected, the method focuses on the inherent characteristics of the object to be detected in principle, and does not depend on the application program running on the object to be detected, so that the decoupling of the detection mode and the application program running on the object to be detected can be realized, the coupling degree is reduced, and the detection logic is simplified.
And secondly, the method does not depend on tools with complex logics such as algorithms and models, and reduces the detection complexity.
And the candidate keyword set can determine the detection accuracy of the detection mode of the application, and when technical personnel collect the candidate keywords in advance to form the candidate keyword set, the detection accuracy of the detection mode of the application can be improved as long as the technical personnel can collect a large number of candidate keywords with high coverage. Therefore, the target keyword set can be updated according to the characteristics of a new simulator on the market after the online detection, so that the timeliness of the target keyword set is matched with the timeliness of the existing simulator on the market, and the high detection accuracy can be kept by the method.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
Fig. 4 is a block diagram of an electronic device 800 shown in the present application. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.
Referring to fig. 4, electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input/output (I/O) interface 812, a sensor component 814, and a communication component 816.
The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operation at the device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, images, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.
The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front-facing camera and/or the rear-facing camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the electronic device 800. For example, the sensor assembly 814 may detect an open/closed state of the device 800, the relative positioning of components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, orientation or acceleration/deceleration of the electronic device 800, and a change in the temperature of the electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi, a carrier network (such as 2G, 3G, 4G, or 5G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives broadcast signals or broadcast operation information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the electronic device 800 to perform the above-described method is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
Fig. 5 is a block diagram of an electronic device 1900 shown in the present application. For example, the electronic device 1900 may be provided as a server.
Referring to fig. 5, electronic device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.
The electronic device 1900 may also include a power component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input/output (I/O) interface 1958. The electronic device 1900 may operate based on an operating system stored in memory 1932, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, or the like.
The embodiments in the present specification are all described in a progressive manner, and each embodiment focuses on differences from other embodiments, and portions that are the same and similar between the embodiments may be referred to each other.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "include", "including" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or terminal device including a series of elements includes not only those elements but also other elements not explicitly listed or inherent to such process, method, article, or terminal device. Without further limitation, an element defined by the phrases "comprising one of \ 8230; \8230;" does not exclude the presence of additional like elements in a process, method, article, or terminal device that comprises the element.
The information processing method and apparatus provided by the present application are introduced in detail, and a specific example is applied in the present application to explain the principle and the implementation of the present application, and the description of the above embodiment is only used to help understand the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (16)
1. An information processing method, characterized in that the method comprises:
acquiring a target keyword set for detecting a simulator, wherein the target keyword set is acquired according to candidate keywords detected in a plurality of preset simulators in a candidate keyword set, and the candidate keyword set comprises a plurality of keywords related to the simulator which are collected in advance;
detecting a target keyword in the target keyword set at a specific storage position of an object to be detected, wherein the specific storage position is obtained according to storage positions for respectively storing the detected candidate keywords in each preset simulator;
counting a second number of the target keywords detected at the specific storage position of the object to be detected respectively under the condition that the target keywords in the target keyword set are detected at the specific storage position of the object to be detected, and acquiring the weight of each target keyword detected at the specific storage position of the object to be detected;
obtaining a simulator evaluation score of the object to be detected according to the second quantity and the weight;
and determining the object to be detected as the simulator under the condition that the evaluation value of the simulator is greater than a preset threshold value.
2. The method of claim 1, further comprising:
detecting any one candidate keyword detected in the plurality of preset simulators in the candidate keyword set on a plurality of real object machines respectively;
counting a first number of real physical machines in which the candidate keyword is detected, among the plurality of real physical machines;
under the condition that the first number is larger than the preset number, the candidate keywords are removed from the candidate keyword set;
and acquiring the target keyword set according to the candidate keywords detected in the plurality of preset simulators in the candidate keyword set after the elimination.
3. The method according to claim 1, wherein said obtaining a simulator rating score for said object to be detected based on said second quantity and said weight comprises:
for any target keyword detected at the specific storage position of the object to be detected, acquiring a keyword score of the target keyword according to the second number of the target keyword detected at the specific storage position of the object to be detected and the weight of the target keyword;
and obtaining the evaluation score of the simulator according to the keyword scores of the target keywords detected at the specific storage position of the object to be detected.
4. The method of claim 1, further comprising:
acquiring a third number of candidate keywords detected in the plurality of preset simulators from any one of the candidate keywords detected in the plurality of preset simulators in the candidate keyword set;
acquiring the weight of the candidate keywords according to the third number of the candidate keywords detected in the plurality of preset simulators;
and forming a corresponding table entry by the candidate keywords and the weights of the candidate keywords, and storing the corresponding table entry in the corresponding relation between the keywords and the weights.
5. The method of claim 4, wherein the obtaining the weight of each target keyword detected at the specific storage location comprises:
and searching weights respectively corresponding to all target keywords detected at a specific storage position of the object to be detected in the corresponding relation between the keywords and the weights.
6. The method of claim 5, further comprising:
and under the condition that the object to be detected is determined to be the simulator, updating the weights respectively corresponding to the target keywords respectively detected at the specific storage position of the object to be detected in the corresponding relation according to the second quantity of the target keywords respectively detected at the specific storage position of the object to be detected.
7. The method of claim 1, further comprising:
under the condition that the object to be detected is determined to be a simulator, detecting the target keywords in the target keyword set at the positions of the object to be detected except the specific storage position;
when the target keywords in the target keyword set are detected at positions of the object to be detected except a specific storage position, adding: a location of the target keyword other than the particular storage location is detected.
8. An information processing apparatus characterized in that the apparatus comprises;
the simulator comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a target keyword set for detecting a simulator, the target keyword set is acquired according to candidate keywords detected in a plurality of preset simulators in a candidate keyword set, and the candidate keyword set comprises a plurality of keywords related to the simulator, which are collected in advance;
the first detection module is used for detecting the target keywords in the target keyword set at a specific storage position of an object to be detected, wherein the specific storage position is obtained according to the storage positions of the detected candidate keywords respectively stored in the preset simulators;
the second counting module is used for counting the second quantity of each target keyword detected at the specific storage position of the object to be detected respectively under the condition that the target keywords in the target keyword set are detected at the specific storage position of the object to be detected;
the third acquisition module is used for acquiring the weight of each target keyword detected at a specific storage position of the object to be detected;
a fourth obtaining module, configured to obtain a simulator rating score of the object to be detected according to the second quantity and the weight;
and the determining module is used for determining the object to be detected as the simulator under the condition that the evaluation value of the simulator is greater than a preset threshold value.
9. The apparatus of claim 8, further comprising:
a second detection module, configured to detect, on a plurality of real object machines, a candidate keyword for any one of the candidate keywords detected in the plurality of preset simulators in the candidate keyword set, respectively;
the first statistical module is used for counting a first number of real physical machines of the candidate keywords in the plurality of real object machines;
the removing module is used for removing the candidate keywords from the candidate keyword set under the condition that the first number is larger than the preset number;
and the second acquisition module is used for acquiring the target keyword set according to the candidate keywords detected in the plurality of preset simulators in the candidate keyword set after being removed.
10. The apparatus of claim 8, wherein the fourth obtaining module comprises:
a first obtaining unit, configured to, for any one target keyword detected at a specific storage location of the object to be detected, obtain a keyword score of the target keyword according to a second number of the target keyword detected at the specific storage location of the object to be detected and a weight of the target keyword;
and the second acquisition unit is used for acquiring the evaluation score of the simulator according to the keyword scores of the target keywords detected at the specific storage position of the object to be detected.
11. The apparatus of claim 8, further comprising:
a fifth obtaining module, configured to obtain, for any one candidate keyword detected in the plurality of preset simulators in the candidate keyword set, a third number of the candidate keywords detected in the plurality of preset simulators;
a sixth obtaining module, configured to obtain a weight of the candidate keyword according to a third number of the candidate keywords detected in the multiple preset simulators;
and the storage module is used for forming a corresponding table entry by the candidate keywords and the weights of the candidate keywords and storing the corresponding table entry in the corresponding relation between the keywords and the weights.
12. The apparatus of claim 11, wherein the third obtaining module is specifically configured to: and searching weights respectively corresponding to all target keywords detected at a specific storage position of the object to be detected in the corresponding relation between the keywords and the weights.
13. The apparatus of claim 12, further comprising:
and the updating module is used for updating the weights respectively corresponding to the target keywords respectively detected at the specific storage position of the object to be detected in the corresponding relation according to the second quantity of the target keywords respectively detected at the specific storage position of the object to be detected under the condition that the object to be detected is determined to be the simulator.
14. The apparatus of claim 9, further comprising:
the third detection module is used for detecting the target keywords in the target keyword set at the positions of the object to be detected except the specific storage position under the condition that the object to be detected is determined to be a simulator;
an adding module, configured to add, in a specific storage location, when a target keyword in the target keyword set is detected in a location of the object to be detected other than the specific storage location: a location of the target keyword other than the particular storage location is detected.
15. An electronic device, characterized in that the electronic device comprises:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the information processing method of any one of claims 1 to 8.
16. A non-transitory computer-readable storage medium in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform the information processing method of any one of claims 1 to 8.
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