CN113176979B - Application program abnormity monitoring method and device, computer equipment and storage medium - Google Patents
Application program abnormity monitoring method and device, computer equipment and storage medium Download PDFInfo
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
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- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/451—Execution arrangements for user interfaces
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
Abstract
The application relates to the field of safety monitoring, and discloses an application program abnormity monitoring method, an application program abnormity monitoring device, computer equipment and a storage medium, wherein the application program abnormity monitoring method comprises the following steps: analyzing a service access request of an application program and determining a target service; sending an operation instruction to a target server corresponding to the target service, so that the target server acquires a snapshot image of the target service; receiving an execution result returned by the target server, and intercepting an operation interface of the application program according to the execution result to obtain an interface image of the application program; using a preset sliding window to simultaneously slide in the snapshot image and the interface image to obtain a plurality of first sliding areas in the snapshot image and a plurality of second sliding areas in the interface image; comparing the plurality of first sliding areas with the corresponding second sliding areas to obtain a plurality of comparison results; and monitoring the abnormity of the application program according to a plurality of comparison results. The application program monitoring efficiency is improved.
Description
Technical Field
The present application relates to the field of security monitoring, and in particular, to a method and an apparatus for monitoring application program exception, a computer device, and a storage medium.
Background
Monitoring is a main means for ensuring normal and stable operation of the service, and the monitoring system can find abnormality and give an alarm in time when the service is in on-line operation, so that operation and maintenance personnel can perform corresponding follow-up processing aiming at the abnormality, and further ensure the stability of the service. A unified application service platform generally needs to access an external service, i.e., a third-party service, to complete a corresponding service business process. When the accessed external service is abnormal, the application program service platform is abnormal for the user, so that the normal display of the accessed external service is ensured.
Currently, external service state monitoring is mainly performed in a service dial test mode. However, since the service dial testing mode is single and has no pertinence, when the service content changes, namely when different external services are faced, the service dial testing cannot timely judge the problem, and early warning is given. The monitoring efficiency can be improved by using professional operation and maintenance personnel to monitor the external service, but the labor cost is increased.
Disclosure of Invention
In view of the foregoing, it is desirable to provide an application program exception monitoring method, apparatus, computer device and storage medium, which can improve efficiency of application program exception monitoring.
A first aspect of the present application provides an application program exception monitoring method, where the application program exception monitoring method includes:
responding to a service access request of an application program, analyzing the service access request, and determining a target service corresponding to the service access request;
sending an operation instruction to a target server corresponding to the target service, so that the target server obtains a snapshot image of the target service according to the operation instruction;
receiving an execution result returned after the target server analyzes the operation instruction, and intercepting an operation interface of an application program according to the execution result to obtain an interface image of the application program;
using a preset sliding window to simultaneously slide in the snapshot image and the interface image to obtain a plurality of first sliding areas in the snapshot image and a plurality of second sliding areas in the interface image, wherein the first sliding areas correspond to the second sliding areas one to one;
comparing the plurality of first sliding areas with the corresponding second sliding areas to obtain a plurality of comparison results;
and carrying out abnormity monitoring on the application program according to the comparison results.
According to an optional embodiment of the present application, the comparing the plurality of first sliding regions and the corresponding second sliding regions to obtain a plurality of comparison results includes:
determining a first page keyword in each first sliding region and a second page keyword in the second sliding region corresponding to the first sliding region;
performing keyword comparison on the first page keywords and the corresponding second page keywords to obtain a plurality of keyword matching degrees;
judging whether the matching degree of each keyword exceeds a preset matching degree threshold value;
and obtaining a plurality of comparison results of the first sliding areas and the corresponding second sliding areas according to the judgment result.
According to an optional embodiment of the present application, the comparing the plurality of first sliding regions and the corresponding second sliding regions includes:
generating a plurality of first images according to each first sliding region, and generating a plurality of second images according to a second sliding region corresponding to each first sliding region, wherein the first images correspond to the second images one by one;
determining a first contrast contour in the first image and a corresponding second contrast contour in the second image;
and comparing the first image with the second image according to the first comparison contour and the second comparison contour.
According to an alternative embodiment of the present application, the determining the first contrast profile in the first image comprises:
detecting all contours in the first image and determining each contour as a first contour;
determining four vertex coordinates of the first contour;
determining horizontally adjacent first contours based on the vertex coordinates, calculating lateral spacing of the horizontally adjacent first contours;
determining vertically adjacent first contours based on the vertex coordinates, and calculating longitudinal spacing of the vertically adjacent first rectangular contours;
and correcting the first contour according to the transverse spacing and the longitudinal spacing to obtain a first comparison contour corresponding to the first contour.
According to an alternative embodiment of the present application, said modifying said first profile according to said lateral spacing and said longitudinal spacing to obtain a first comparison profile corresponding to said first profile comprises:
determining the transverse spacing between two horizontally adjacent first profiles and the longitudinal spacing between two vertically adjacent first profiles;
merging the first profile according to the transverse and longitudinal spacings;
and taking the merged first profile as the first comparison profile.
According to an alternative embodiment of the present application, the method further comprises:
when the application program is judged to be normal according to the comparison results, acquiring target display time corresponding to the target service;
determining the time for obtaining the interface image of the application program;
calculating the time difference between the time of obtaining the interface image of the application program and the target display time;
when the time difference is larger than a preset time threshold, determining that the service state corresponding to the application program is abnormal; and when the time difference is equal to or smaller than the preset time threshold, determining that the service state corresponding to the application program is normal.
According to an optional embodiment of the present application, the parsing the service access request and determining a target service corresponding to the service access request includes:
acquiring a request message of the service access request;
acquiring a message segmentation identifier corresponding to service information from a configuration label library;
segmenting the request message based on the message segmentation identifier to obtain service parameters corresponding to the service access request;
inquiring a preset parameter mapping table, determining service items according to the service parameters, and determining the service items as target services corresponding to the service access requests;
the parameter mapping table comprises a mapping relation between service parameters and service items.
A second aspect of the present application provides an application exception monitoring apparatus, the apparatus comprising:
the request analysis module is used for responding to a service access request of an application program, analyzing the service access request and determining a target service corresponding to the service access request;
the instruction sending module is used for sending an operation instruction to a target server corresponding to the target service, so that the target server obtains a snapshot image of the target service according to the operation instruction;
the result analysis module is used for receiving an execution result returned after the target server analyzes the operation instruction, and intercepting an operation interface of an application program according to the execution result to obtain an interface image of the application program;
the image processing module is used for simultaneously sliding in the snapshot image and the interface image by using a preset sliding window to obtain a plurality of first sliding areas in the snapshot image and a plurality of second sliding areas in the interface image, wherein the first sliding areas correspond to the second sliding areas one to one;
the region comparison module is used for comparing the plurality of first sliding regions with the corresponding second sliding regions to obtain a plurality of comparison results;
and the abnormity monitoring module is used for monitoring the abnormity of the application program according to the comparison results.
A third aspect of the application provides a computer device comprising a memory and a processor; the memory is used for storing a computer program; the processor is used for implementing the application program abnormity monitoring method when the computer program is executed.
A fourth aspect of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the application program exception monitoring method as described above.
The embodiment of the application discloses a method and a device for monitoring application program abnormity, computer equipment and a storage medium, wherein the method comprises the steps of responding to an access request of an application program, analyzing the service access request and determining a target service corresponding to the service access request; then, an operation instruction is sent to a target server corresponding to the target service, so that the target server obtains a snapshot image of the target service according to the operation instruction; then receiving an execution result returned after the target server analyzes the operation instruction, and intercepting an operation interface of an application program according to the execution result to obtain an interface image of the application program; sliding in the snapshot image and the interface image simultaneously by using a preset sliding window to obtain a plurality of first sliding areas in the snapshot image and a plurality of second sliding areas in the interface image, wherein the first sliding areas correspond to the second sliding areas one by one, and the plurality of first sliding areas and the plurality of second sliding areas are obtained through the preset sliding window, so that the comparison speed can be increased; comparing the plurality of first sliding areas with the corresponding second sliding areas to obtain a plurality of comparison results; and finally, carrying out abnormity monitoring on the application program according to the comparison results, thereby effectively improving the monitoring efficiency of the application program.
Drawings
Fig. 1 is a schematic flowchart of an application exception monitoring method according to an embodiment of the present application;
FIG. 2 is a schematic block diagram of an application exception monitoring apparatus according to an embodiment of the present application;
fig. 3 is a schematic block diagram of a structure of a computer device according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The flow diagrams depicted in the figures are merely illustrative and do not necessarily include all of the elements and operations/steps, nor do they necessarily have to be performed in the order depicted. For example, some operations/steps may be decomposed, combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The embodiment of the application program abnormity monitoring method and device, computer equipment and computer readable storage medium. The application program abnormity monitoring method can be applied to terminal equipment or a server, the terminal equipment can be electronic equipment such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant and wearable equipment, and the server can be a single server or a server cluster consisting of a plurality of servers. The following explains the application program exception monitoring method applied to a server as an example.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
Referring to fig. 1, fig. 1 is a schematic flowchart of an application exception monitoring method according to an embodiment of the present disclosure.
As shown in fig. 1, the application program exception monitoring method specifically includes steps S11 to S16, and the order of the steps in the flowchart may be changed or some of the steps may be omitted according to different requirements.
S11, responding to a service access request of an application program, analyzing the service access request, and determining a target service corresponding to the service access request.
Illustratively, when a user clicks an external service button in an application program, the client generates a service access request corresponding to the external service. For example, when a user clicks a button of an external service in a user interface of an application service platform, a service access request corresponding to the external service is generated. The service access request may include a Hypertext Transfer Protocol (HTTP) request.
In some embodiments, the parsing the service access request and determining a target service corresponding to the service access request includes:
acquiring a request message of the service access request;
acquiring a message segmentation identifier corresponding to service information from a configuration label library;
dividing the request message based on the message division identifier to obtain service parameters corresponding to the service access request;
inquiring a preset parameter mapping table, determining service items according to the service parameters, and determining the service items as target services corresponding to the service access requests;
the parameter mapping table comprises a mapping relation between service parameters and service items.
Illustratively, a configuration tag library is preset, and the configuration tag library stores message segmentation identifiers corresponding to a plurality of kinds of information, such as message segmentation identifiers corresponding to service information. The message segmentation identifier is used for identifying the position of cutting in the message. And based on the position of the message segmentation identifier, segmenting the request message to obtain service parameters corresponding to the service access request.
And determining a target service corresponding to the service access request according to a preset parameter mapping table and a mapping relation between service parameters and service items. By presetting the message segmentation identifier, the speed and the accuracy of determining the service parameters can be improved, so that the speed and the accuracy of determining the target service corresponding to the service access request are improved.
S12, sending an operation instruction to a target server corresponding to the target service, so that the target server obtains a snapshot image of the target service according to the operation instruction.
Determining a target server corresponding to the target service, and sending an operation instruction to the target server, wherein the operation instruction is used for controlling the target server to obtain a snapshot image corresponding to the target service, and the snapshot image is a display image of the target service when the target service is normally opened in an application program.
And S13, receiving an execution result returned after the target server analyzes the operation instruction, and intercepting an operation interface of an application program according to the execution result to obtain an interface image of the application program.
And receiving an execution result returned after the target server analyzes the operation instruction, namely receiving a snapshot image of the target service acquired by the target server according to the operation instruction. And after receiving the snapshot image, intercepting an operation interface of an application program according to the execution result to obtain an interface image corresponding to the application program. The interface image is a current display image of the target service in an application program.
S14, sliding in the snapshot image and the interface image simultaneously by using a preset sliding window to obtain a plurality of first sliding areas in the snapshot image and a plurality of second sliding areas in the interface image, wherein the first sliding areas correspond to the second sliding areas one to one.
For example, sliding windows corresponding to different image pixels may be preset. For example, an image with small image pixels may have a small sliding window, and an image with large image pixels may have a large sliding window. Different sliding windows are set according to different image pixels, so that enough first sliding areas and enough second sliding areas can be obtained, subsequent comparison is facilitated, and the effectiveness of monitoring of the application program is improved.
S15, comparing the plurality of first sliding areas with the corresponding second sliding areas to obtain a plurality of comparison results.
Exemplarily, determining a region element in each of the first sliding regions, resulting in a plurality of first region elements; determining the area elements in each second sliding area to obtain a plurality of second area elements, wherein the first area elements correspond to the second area elements one to one, and comparing each first area element with the corresponding second area element to obtain a plurality of comparison results.
For example, the obtained multiple alignment results may be stored in the blockchain.
In some embodiments, the comparing the plurality of first sliding regions and the corresponding second sliding regions to obtain a plurality of comparison results includes:
determining a first page keyword in each first sliding region and a second page keyword in the second sliding region corresponding to the first sliding region;
performing keyword comparison on the first page keywords and the corresponding second page keywords to obtain a plurality of keyword matching degrees;
judging whether the matching degree of each keyword exceeds a preset matching degree threshold value;
and obtaining a plurality of comparison results of the first sliding areas and the corresponding second sliding areas according to the judgment result.
Illustratively, the judgment result of whether the matching degree of each keyword exceeds a preset matching degree threshold is used as a plurality of comparison results of the plurality of first sliding regions and the corresponding second sliding regions. Specifically, determining whether the keyword matching degree corresponding to each comparison result exceeds a preset matching degree threshold, calculating the number of the comparison results of which the keyword matching degrees exceed the preset matching degree threshold, and determining that the service state corresponding to the application program is normal when the number of the comparison results is greater than or equal to the preset threshold; and when the number of the comparison results is smaller than the preset threshold value, determining that the service state corresponding to the application program is abnormal. Illustratively, the matching degree may include a similarity degree.
In some embodiments, the aligning the plurality of first sliding regions and the corresponding second sliding regions comprises:
generating a plurality of first images according to each first sliding region, and generating a plurality of second images according to a second sliding region corresponding to each first sliding region, wherein the first images correspond to the second images one by one;
determining a first contrast profile in the first image and a corresponding second contrast profile in the second image;
and comparing the first image with the second image according to the first comparison contour and the second comparison contour.
For example, the snapshot image may be cut according to an edge of the first sliding region to obtain a plurality of first images; the interface image may be cut according to an edge of the second sliding region to obtain a plurality of second images.
And comparing the first comparison contour in the first image with the second comparison contour in the second image to obtain a comparison result of the first image and the second image. The first contrast outline may be a character frame corresponding to the character in the first image, and the second contrast outline may be a character frame corresponding to the character in the second image.
And comparing the first comparison outline corresponding to the first image with the second comparison outline corresponding to the second image, and taking the comparison result as the comparison result of the first image and the second image, so that the comparison efficiency can be improved, and the monitoring efficiency of the application program can be improved.
In some embodiments, the determining the first contrast profile in the first image comprises:
detecting all contours in the first image and determining each contour as a first contour;
determining four vertex coordinates of the first contour;
determining horizontally adjacent first contours based on the vertex coordinates, calculating lateral spacing of the horizontally adjacent first contours;
determining vertically adjacent first contours based on the vertex coordinates, and calculating longitudinal spacing of the vertically adjacent first rectangular contours;
and correcting the first contour according to the transverse spacing and the longitudinal spacing to obtain a first comparison contour corresponding to the first contour.
Illustratively, all characters in the first image are detected, a character border corresponding to each character is determined, the character border is determined as a first contour, and a plurality of first contours are obtained. And determining four vertex coordinates corresponding to each first contour, and determining the length and the width of each first contour according to the vertex coordinates. And determining the area of the profile corresponding to each first profile according to the length and the width of each first profile.
Based on the vertex coordinates of a first contour, a first contour horizontally adjacent to the first contour is determined, and the transverse distance between two horizontally adjacent first contours is calculated. The first contour B is determined to be horizontally adjacent to the first contour a, e.g. from the vertex coordinates of the first contour a, i.e. the first contour horizontally adjacent to the first contour a is determined to be the first contour B from the vertex coordinates of the first contour a, the lateral distance between the first contour a and the first contour B is calculated.
Based on the vertex coordinates of a first contour, a first contour vertically adjacent to the first contour is determined, and the longitudinal distance between two vertically adjacent first contours is calculated. For example, according to the vertex coordinates of the first contour A, a first contour C is determined to be vertically adjacent to the first contour A, namely, according to the vertex coordinates of the first contour A, the first contour vertically adjacent to the first contour A is determined to be the first contour C, and the longitudinal distance between the first contour A and the first contour C is calculated.
Illustratively, the first profile is modified according to the profile area, the transverse spacing and the longitudinal spacing, for example, the first profile is merged, removed, split, and the like, so as to obtain a first comparison profile corresponding to the first profile. Wherein the first comparison contour may comprise a plurality of contours, the first comparison contour being used to perform a data comparison.
In some embodiments, said modifying said first profile according to said lateral spacing and said longitudinal spacing to obtain a first comparison profile corresponding to said first profile comprises:
determining a transverse interval between two horizontally adjacent first profiles and a longitudinal interval between two vertically adjacent first profiles;
merging the first profile according to the transverse and longitudinal spacings;
and taking the merged first contour as the first comparison contour.
Exemplarily, searching for the first contours with the transverse spacing smaller than a preset transverse threshold, and combining the first contours with the transverse spacing smaller than the preset transverse threshold to obtain second contours; and searching the second contour with the longitudinal distance smaller than a preset longitudinal threshold value, combining the second contours to obtain a third contour, and taking the third contour as the first comparison contour.
For example, the first contour a is horizontally adjacent to the first contour B, and the lateral distance between the first contour a and the first contour B is smaller than a preset lateral threshold, the first contour a and the first contour B are combined to obtain a second contour C; and combining the first contour E and the first contour F to obtain a second contour G, wherein the first contour E is vertically adjacent to the first contour F, and the longitudinal distance between the first contour E and the first contour F is smaller than a preset transverse threshold value.
The first comparison contour is obtained by combining the first contours, so that the number of comparison works can be reduced, and the comparison work speed is increased.
For example, the third profile may be continuously processed, so that the lateral distance between two horizontally adjacent first comparison profiles in the obtained first comparison profiles is greater than or equal to a preset lateral threshold; the longitudinal distance between two vertically adjacent first contrast profiles is greater than or equal to a preset longitudinal threshold.
For example, if the lateral distance between two horizontally adjacent third profiles is smaller than a preset lateral threshold, combining the third profiles with the lateral distance smaller than the preset lateral threshold to obtain a fourth profile; and if the longitudinal distance between two vertically adjacent fourth profiles is smaller than a preset longitudinal threshold, combining the fourth profiles with the longitudinal distance smaller than the preset longitudinal threshold to obtain a fifth profile.
Through further processing of the third contour, the number of comparison works can be further reduced, and the comparison work speed is further increased.
And S16, carrying out abnormity monitoring on the application program according to the comparison results.
Illustratively, the application program is monitored for an exception according to a comparison result of keywords in the plurality of first sliding areas and the corresponding second sliding areas. Specifically, determining whether the keyword matching degree corresponding to each comparison result exceeds a preset matching degree threshold, calculating the number of the comparison results of which the keyword matching degree exceeds the preset matching degree threshold, and determining that the service state corresponding to the application program is normal when the number of the comparison results is greater than or equal to the preset threshold; and when the number of the comparison results is smaller than the preset threshold value, determining that the service state corresponding to the application program is abnormal.
In some embodiments, the method further comprises:
when the application program is judged to be normal according to the comparison results, acquiring target display time corresponding to the target service;
determining the time for obtaining the interface image of the application program;
calculating the time difference between the time of obtaining the interface image of the application program and the target display time;
when the time difference is larger than a preset time threshold, determining that the service state corresponding to the application program is abnormal; and when the time difference is equal to or smaller than the preset time threshold, determining that the service state corresponding to the application program is normal.
And when the application program is judged to be normal according to the comparison results, acquiring the target display time of the target service opened under the normal condition. For example, the target display time corresponding to the target service may be obtained by adding the time of receiving the service access request to the receiving time corresponding to the target service.
When the time difference value between the time of obtaining the interface image of the application program and the target display time is larger than a preset time threshold value, determining that the opening time of the target service is too slow, and determining that the service state corresponding to the application program is abnormal; and when the time difference between the time of obtaining the interface image of the application program and the target display time is smaller than or equal to the preset time threshold, determining that the opening time of the target service is normal, and determining that the service state corresponding to the application program is normal.
Through setting the snapshot picture and the interface image for comparison, and judging the target service response time and the like twice, double judgment is realized, the accuracy of monitoring the application program is ensured, and the efficiency of monitoring the application program is improved.
In the method for monitoring application program exception provided in the above embodiment, the service access request is analyzed by responding to the access request of the application program, and a target service corresponding to the service access request is determined; then, an operation instruction is sent to a target server corresponding to the target service, so that the target server obtains a snapshot image of the target service according to the operation instruction; then receiving an execution result returned after the target server analyzes the operation instruction, and intercepting an operation interface of an application program according to the execution result to obtain an interface image of the application program; sliding in the snapshot image and the interface image simultaneously by using a preset sliding window to obtain a plurality of first sliding areas in the snapshot image and a plurality of second sliding areas in the interface image, wherein the first sliding areas correspond to the second sliding areas one by one, and the plurality of first sliding areas and the plurality of second sliding areas are obtained through the preset sliding window, so that the comparison speed can be increased; comparing the plurality of first sliding areas with the corresponding second sliding areas to obtain a plurality of comparison results; and finally, carrying out abnormity monitoring on the application program according to the comparison results, thereby effectively improving the monitoring efficiency of the application program.
Referring to fig. 2, fig. 2 is a schematic block diagram of an application exception monitoring apparatus according to an embodiment of the present application, where the application exception monitoring apparatus is configured to execute the foregoing application exception monitoring method. The application program abnormity monitoring device can be configured in a server or a terminal.
The server may be an independent server or a server cluster. The terminal can be an electronic device such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant and a wearable device.
As shown in fig. 2, the application abnormality monitoring apparatus 20 includes: the system comprises a request analysis module 201, an instruction sending module 202, a result analysis module 203, a picture processing module 204, a region comparison module 205 and an abnormity monitoring module 206.
The request parsing module 201 is configured to parse a service access request in response to the service access request of an application, and determine a target service corresponding to the service access request.
Illustratively, when a user clicks an external service button in an application program, the client generates a service access request corresponding to the external service. For example, when a user clicks a button of an external service in a user interface of an application service platform, a service access request corresponding to the external service is generated. The service access request may include a Hypertext Transfer Protocol (HTTP) request.
In some embodiments, the request parsing module 201 parses the service access request, and determining a target service corresponding to the service access request includes:
acquiring a request message of the service access request;
acquiring a message segmentation identifier corresponding to service information from a configuration label library;
segmenting the request message based on the message segmentation identifier to obtain service parameters corresponding to the service access request;
inquiring a preset parameter mapping table, determining service items according to the service parameters, and determining the service items as target services corresponding to the service access requests;
the parameter mapping table comprises a mapping relation between service parameters and service items.
Illustratively, a configuration tag library is preset, and the configuration tag library stores message segmentation identifiers corresponding to a plurality of information, such as message segmentation identifiers corresponding to service information. The message segmentation identifier is used for identifying the position of cutting in the message. And based on the position of the message segmentation identifier, segmenting the request message to obtain the service parameters corresponding to the service access request.
And determining a target service corresponding to the service access request according to a preset parameter mapping table and a mapping relation between service parameters and service items. By presetting the message segmentation identifier, the speed and the accuracy of determining the service parameters can be improved, so that the speed and the accuracy of determining the target service corresponding to the service access request are improved.
The instruction sending module 202 is configured to send an operation instruction to a target server corresponding to the target service, so that the target server obtains a snapshot image of the target service according to the operation instruction.
Determining a target server corresponding to the target service, and sending an operation instruction to the target server, wherein the operation instruction is used for controlling the target server to obtain a snapshot image corresponding to the target service, and the snapshot image is a display image of the target service when the target service is normally opened in an application program.
And the result analysis module 203 is configured to receive an execution result returned after the target server analyzes the operation instruction, and intercept an operation interface of an application program according to the execution result to obtain an interface image of the application program.
And receiving an execution result returned after the target server analyzes the operation instruction, namely receiving a snapshot image of the target service acquired by the target server according to the operation instruction. And after receiving the snapshot image, intercepting an operation interface of an application program according to the execution result to obtain an interface image corresponding to the application program. The interface image is a current display image of the target service in an application program.
The image processing module 204 is configured to slide in the snapshot image and the interface image simultaneously by using a preset sliding window to obtain a plurality of first sliding regions in the snapshot image and a plurality of second sliding regions in the interface image, where the first sliding regions correspond to the second sliding regions one to one.
For example, sliding windows corresponding to different image pixels may be preset. For example, an image with small image pixels may have a small sliding window, and an image with large image pixels may have a large sliding window. Different sliding windows are set according to different image pixels, so that enough first sliding areas and enough second sliding areas can be obtained, subsequent comparison is facilitated, and the effectiveness of monitoring of the application program is improved.
The region comparison module 205 is configured to compare the plurality of first sliding regions with the corresponding second sliding regions to obtain a plurality of comparison results.
Exemplarily, determining a region element in each first sliding region, resulting in a plurality of first region elements; determining the area elements in each second sliding area to obtain a plurality of second area elements, wherein the first area elements correspond to the second area elements one to one, and comparing each first area element with the corresponding second area element to obtain a plurality of comparison results.
In some embodiments, the comparing module 205 compares the first sliding regions with the corresponding second sliding regions to obtain a plurality of comparison results, including:
determining a first page keyword in each first sliding region and a second page keyword in the second sliding region corresponding to the first sliding region;
performing keyword comparison on the first page keywords and the corresponding second page keywords to obtain a plurality of keyword matching degrees;
judging whether the matching degree of each keyword exceeds a preset matching degree threshold value;
and obtaining a plurality of comparison results of the plurality of first sliding areas and the corresponding second sliding areas according to the judgment result.
Illustratively, the determination result of whether the matching degree of each keyword exceeds a preset matching degree threshold is used as a plurality of comparison results of the first sliding regions and the corresponding second sliding regions. Specifically, determining whether the keyword matching degree corresponding to each comparison result exceeds a preset matching degree threshold, calculating the number of the comparison results of which the keyword matching degrees exceed the preset matching degree threshold, and determining that the service state corresponding to the application program is normal when the number of the comparison results is greater than or equal to the preset threshold; and when the number of the comparison results is smaller than the preset threshold value, determining that the service state corresponding to the application program is abnormal. Illustratively, the matching degree may include a similarity degree.
In some embodiments, the region alignment module 205 aligns the first sliding regions and the corresponding second sliding regions by:
generating a plurality of first images according to each first sliding area, and generating a plurality of second images according to a second sliding area corresponding to each first sliding area, wherein the first images correspond to the second images one by one;
determining a first contrast contour in the first image and a corresponding second contrast contour in the second image;
and comparing the first image with the second image according to the first comparison outline and the second comparison outline.
Illustratively, the snapshot image may be cut according to an edge of the first sliding region, so as to obtain a plurality of first images; the interface image may be cut according to an edge of the second sliding region to obtain a plurality of second images.
And comparing the first comparison contour in the first image with the second comparison contour in the second image to obtain a comparison result of the first image and the second image. The first contrast outline may be a character frame corresponding to the character in the first image, and the second contrast outline may be a character frame corresponding to the character in the second image.
And comparing the first comparison outline corresponding to the first image with the second comparison outline corresponding to the second image, and taking the comparison result as the comparison result of the first image and the second image, so that the comparison efficiency can be improved, and the monitoring efficiency of the application program can be improved. In some embodiments, the region alignment module 205 determines the first alignment contour in the first image comprises:
detecting all contours in the first image and determining each contour as a first contour;
determining four vertex coordinates of the first contour;
determining horizontally adjacent first contours based on the vertex coordinates, calculating lateral spacing of the horizontally adjacent first contours;
determining vertically adjacent first contours based on the vertex coordinates, and calculating longitudinal spacing of the vertically adjacent first rectangular contours;
and correcting the first contour according to the transverse spacing and the longitudinal spacing to obtain a first comparison contour corresponding to the first contour.
Illustratively, all characters in the first image are detected, a character border corresponding to each character is determined, the character border is determined as a first contour, and a plurality of first contours are obtained. And determining four vertex coordinates corresponding to each first contour, and determining the length and the width of each first contour according to the vertex coordinates. And determining the area of the profile corresponding to each first profile according to the length and the width of each first profile.
Based on the vertex coordinates of a first contour, a first contour horizontally adjacent to the first contour is determined, and the transverse distance between two horizontally adjacent first contours is calculated. The first contour B is determined to be horizontally adjacent to the first contour a, e.g. from the vertex coordinates of the first contour a, i.e. the first contour horizontally adjacent to the first contour a is determined to be the first contour B from the vertex coordinates of the first contour a, the lateral distance between the first contour a and the first contour B is calculated.
Based on the vertex coordinates of a first contour, a first contour vertically adjacent to the first contour is determined, and the longitudinal distance between two vertically adjacent first contours is calculated. For example, according to the vertex coordinates of the first contour a, a first contour C is determined to be vertically adjacent to the first contour a, that is, according to the vertex coordinates of the first contour a, the first contour vertically adjacent to the first contour a is determined to be the first contour C, and the longitudinal distance between the first contour a and the first contour C is calculated.
Illustratively, the first profile is corrected according to the profile area, the transverse spacing and the longitudinal spacing, for example, the first profile is merged, removed, split, and the like, so as to obtain a first comparison profile corresponding to the first profile. Wherein the first comparison profile may comprise a plurality of profiles, and the first comparison profile is used for data comparison.
In some embodiments, the region comparison module 205 modifies the first contour according to the transverse pitch and the longitudinal pitch, and obtaining a first comparison contour corresponding to the first contour includes:
determining the transverse spacing between two horizontally adjacent first profiles and the longitudinal spacing between two vertically adjacent first profiles;
merging the first profile according to the transverse and longitudinal spacings;
and taking the merged first contour as the first comparison contour.
Exemplarily, searching for the first contours with the transverse spacing smaller than a preset transverse threshold, and combining the first contours with the transverse spacing smaller than the preset transverse threshold to obtain second contours; and searching the second contour with the longitudinal distance smaller than a preset longitudinal threshold value, combining the second contours to obtain a third contour, and taking the third contour as the first comparison contour.
For example, the first contour a is horizontally adjacent to the first contour B, and the lateral distance between the first contour a and the first contour B is smaller than a preset lateral threshold, the first contour a and the first contour B are combined to obtain a second contour C; and combining the first contour E and the first contour F to obtain a second contour G, wherein the first contour E is vertically adjacent to the first contour F, and the longitudinal distance between the first contour E and the first contour F is smaller than a preset transverse threshold value.
The first comparison contour is obtained by combining the first contours, so that the number of comparison works can be reduced, and the comparison work speed is increased.
For example, the third profile may be continuously processed, so that the lateral distance between two horizontally adjacent first comparison profiles in the obtained first comparison profiles is greater than or equal to a preset lateral threshold; the longitudinal distance between two vertically adjacent first contrast profiles is greater than or equal to a preset longitudinal threshold.
For example, if the lateral distance between two horizontally adjacent third profiles is smaller than a preset lateral threshold, combining the third profiles with the lateral distance smaller than the preset lateral threshold to obtain a fourth profile; and if the longitudinal distance between two vertically adjacent fourth profiles is smaller than a preset longitudinal threshold, combining the fourth profiles of which the longitudinal distance is smaller than the preset longitudinal threshold to obtain a fifth profile.
Through further processing of the third contour, the number of comparison works can be further reduced, and the comparison work speed is further increased.
An anomaly monitoring module 206, configured to perform anomaly monitoring on the application program according to the multiple comparison results.
Illustratively, the application program is monitored for abnormalities according to keyword comparison results of the plurality of first sliding areas and the corresponding second sliding areas. Specifically, determining whether the keyword matching degree corresponding to each comparison result exceeds a preset matching degree threshold, calculating the number of the comparison results of which the keyword matching degree exceeds the preset matching degree threshold, and determining that the service state corresponding to the application program is normal when the number of the comparison results is greater than or equal to the preset threshold; and when the number of the comparison results is smaller than the preset threshold value, determining that the service state corresponding to the application program is abnormal.
In some embodiments, the anomaly monitoring module 206 is further configured to: when the application program is judged to be normal according to the comparison results, acquiring target display time corresponding to the target service; determining the time for obtaining the interface image of the application program; calculating the time difference between the time of obtaining the interface image of the application program and the target display time; when the time difference is larger than a preset time threshold, determining that the service state corresponding to the application program is abnormal; and when the time difference is equal to or smaller than the preset time threshold, determining that the service state corresponding to the application program is normal.
And when the application program is judged to be normal according to the comparison results, acquiring the target display time of the opened target service under the normal condition. For example, the target display time corresponding to the target service may be obtained by adding the time of receiving the service access request to the receiving time corresponding to the target service.
When the time difference value between the time of obtaining the interface image of the application program and the target display time is larger than a preset time threshold value, determining that the opening time of the target service is too slow, and determining that the service state corresponding to the application program is abnormal; and when the time difference between the time of obtaining the interface image of the application program and the target display time is less than or equal to the preset time threshold, determining that the opening time of the target service is normal, and determining that the service state corresponding to the application program is normal.
Through setting the snapshot picture and the interface image for comparison, and judging the target service response time and the like twice, double judgment is realized, the accuracy of monitoring the application program is ensured, and the efficiency of monitoring the application program is improved.
The application program abnormality monitoring apparatus provided in the above embodiment may be implemented in a form of a computer program, and the computer program may be run on a computer device as shown in fig. 3.
Referring to fig. 3, fig. 3 is a schematic block diagram of a computer device according to an embodiment of the present disclosure. The computer device may be a server or a terminal device.
As shown in fig. 3, the computer device 30 includes a processor 301 and a memory 302 connected by a system bus, wherein the memory 302 may include a nonvolatile storage medium and a volatile storage medium.
The processor 301 is used to provide computing and control capabilities that support the operation of the overall computer device.
The memory 302 may store an operating system and computer programs. The computer program comprises program instructions which, when executed, cause the processor 301 to perform the application program exception monitoring method described herein.
In a possible embodiment, the computer device further comprises a network interface for performing network communication, such as sending assigned tasks, etc. Those skilled in the art will appreciate that the architecture shown in fig. 3 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
It should be understood that Processor 301 is a Central Processing Unit (CPU), which may also be other general purpose processors, digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Wherein, in one embodiment, the processor executes a computer program stored in the memory to implement the steps of:
responding to a service access request of an application program, analyzing the service access request, and determining a target service corresponding to the service access request; sending an operation instruction to a target server corresponding to the target service, so that the target server obtains a snapshot image of the target service according to the operation instruction; receiving an execution result returned after the target server analyzes the operation instruction, and intercepting an operation interface of an application program according to the execution result to obtain an interface image of the application program; simultaneously sliding in the snapshot image and the interface image by using a preset sliding window to obtain a plurality of first sliding areas in the snapshot image and a plurality of second sliding areas in the interface image, wherein the first sliding areas correspond to the second sliding areas one to one; comparing the plurality of first sliding areas with the corresponding second sliding areas to obtain a plurality of comparison results; and monitoring the abnormity of the application program according to the comparison results.
Specifically, the specific implementation method of the processor for the instruction may refer to the description of the relevant steps in the foregoing embodiment of the application program exception monitoring method, which is not described herein again.
Embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, where the computer program includes program instructions, and a method implemented when the program instructions are executed may refer to the embodiments of the application program anomaly monitoring method in the present application.
The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiment, for example, a hard disk or a memory of the computer device. The computer readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the computer device.
Further, the computer-readable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to use of the computer device, and the like.
In the method, the apparatus, the computer device, and the computer-readable storage medium for monitoring application program exceptions provided in the foregoing embodiments, the service access request is analyzed by responding to the access request of the application program, and a target service corresponding to the service access request is determined; then, an operation instruction is sent to a target server corresponding to the target service, so that the target server obtains a snapshot image of the target service according to the operation instruction; then receiving an execution result returned after the target server analyzes the operation instruction, and intercepting an operation interface of an application program according to the execution result to obtain an interface image of the application program; sliding in the snapshot image and the interface image simultaneously by using a preset sliding window to obtain a plurality of first sliding areas in the snapshot image and a plurality of second sliding areas in the interface image, wherein the first sliding areas correspond to the second sliding areas one by one, and the plurality of first sliding areas and the plurality of second sliding areas are obtained through the preset sliding window, so that the comparison speed can be increased; comparing the plurality of first sliding areas with the corresponding second sliding areas to obtain a plurality of comparison results; and finally, carrying out abnormity monitoring on the application program according to the comparison results, thereby effectively improving the monitoring efficiency of the application program.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
It is also to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments. The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think of various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (9)
1. An application program exception monitoring method, characterized in that the application program exception monitoring method comprises:
responding to a service access request of an application program, analyzing the service access request, and determining a target service corresponding to the service access request;
sending an operation instruction to a target server corresponding to the target service, so that the target server obtains a snapshot image of the target service according to the operation instruction;
receiving an execution result returned after the target server analyzes the operation instruction, and intercepting an operation interface of an application program according to the execution result to obtain an interface image of the application program;
using a preset sliding window to simultaneously slide in the snapshot image and the interface image to obtain a plurality of first sliding areas in the snapshot image and a plurality of second sliding areas in the interface image, wherein the first sliding areas correspond to the second sliding areas one to one;
comparing the plurality of first sliding areas with the corresponding second sliding areas to obtain a plurality of comparison results;
monitoring the application program for abnormity according to the comparison results;
when the application program is judged to be normal according to the comparison results, acquiring target display time corresponding to the target service;
determining the time for obtaining the interface image of the application program;
calculating the time difference between the time of obtaining the interface image of the application program and the target display time;
when the time difference is larger than a preset time threshold, determining that the service state corresponding to the application program is abnormal; and when the time difference is equal to or smaller than the preset time threshold, determining that the service state corresponding to the application program is normal.
2. The method for monitoring application program exceptions according to claim 1, wherein the comparing the plurality of first sliding regions with the corresponding second sliding regions to obtain a plurality of comparison results comprises:
determining a first page keyword in each first sliding region and a second page keyword in the second sliding region corresponding to the first sliding region;
performing keyword comparison on the first page keywords and the corresponding second page keywords to obtain a plurality of keyword matching degrees;
judging whether the matching degree of each keyword exceeds a preset matching degree threshold value;
and obtaining a plurality of comparison results of the first sliding areas and the corresponding second sliding areas according to the judgment result.
3. The method for monitoring application program exceptions according to claim 1, wherein the comparing the plurality of first sliding regions to the corresponding second sliding regions comprises:
generating a plurality of first images according to each first sliding area, and generating a plurality of second images according to a second sliding area corresponding to each first sliding area, wherein the first images correspond to the second images one by one;
determining a first contrast contour in the first image and a corresponding second contrast contour in the second image;
and comparing the first image with the second image according to the first comparison contour and the second comparison contour.
4. The application anomaly monitoring method of claim 3, wherein said determining a first contrast profile in said first image comprises:
detecting all contours in the first image and determining each contour as a first contour;
determining four vertex coordinates of the first contour;
determining horizontally adjacent first contours based on the vertex coordinates, calculating lateral spacing of the horizontally adjacent first contours;
determining vertically adjacent first contours based on the vertex coordinates, and calculating longitudinal spacing of the vertically adjacent first rectangular contours;
and correcting the first contour according to the transverse spacing and the longitudinal spacing to obtain a first comparison contour corresponding to the first contour.
5. The method for monitoring application program anomalies according to claim 4, wherein the modifying the first profile according to the lateral spacing and the longitudinal spacing to obtain a first comparison profile corresponding to the first profile includes:
determining the transverse spacing between two horizontally adjacent first profiles and the longitudinal spacing between two vertically adjacent first profiles;
merging the first profile according to the transverse and longitudinal spacings;
and taking the merged first profile as the first comparison profile.
6. The method for monitoring application program exceptions according to claim 1, wherein the parsing the service access request and determining a target service corresponding to the service access request comprises:
acquiring a request message of the service access request;
acquiring a message segmentation identifier corresponding to service information from a configuration label library;
segmenting the request message based on the message segmentation identifier to obtain service parameters corresponding to the service access request;
inquiring a preset parameter mapping table, determining service items according to the service parameters, and determining the service items as target services corresponding to the service access requests;
the parameter mapping table includes mapping relationship between service parameters and service items.
7. An application exception monitoring apparatus, comprising:
the request analysis module is used for responding to a service access request of an application program, analyzing the service access request and determining a target service corresponding to the service access request;
the instruction sending module is used for sending an operation instruction to a target server corresponding to the target service, so that the target server obtains a snapshot image of the target service according to the operation instruction;
the result analysis module is used for receiving an execution result returned after the target server analyzes the operation instruction, and intercepting an operation interface of an application program according to the execution result to obtain an interface image of the application program;
the image processing module is used for simultaneously sliding in the snapshot image and the interface image by using a preset sliding window to obtain a plurality of first sliding areas in the snapshot image and a plurality of second sliding areas in the interface image, wherein the first sliding areas correspond to the second sliding areas one to one;
the region comparison module is used for comparing the plurality of first sliding regions with the corresponding second sliding regions to obtain a plurality of comparison results;
the anomaly monitoring module is used for monitoring the anomaly of the application program according to the comparison results; when the application program is judged to be normal according to the comparison results, acquiring target display time corresponding to the target service; determining the time for obtaining the interface image of the application program; calculating the time difference between the time of obtaining the interface image of the application program and the target display time; when the time difference value is larger than a preset time threshold value, determining that the service state corresponding to the application program is abnormal; and when the time difference is equal to or smaller than the preset time threshold, determining that the service state corresponding to the application program is normal.
8. A computer device, wherein the computer device comprises a memory and a processor;
the memory for storing a computer program;
the processor, when executing the computer program, is configured to implement the application program exception monitoring method according to any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the application program anomaly monitoring method according to any one of claims 1 to 6.
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