[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

CN115965460A - Abnormal service identification method and device, computer equipment and storage medium - Google Patents

Abnormal service identification method and device, computer equipment and storage medium Download PDF

Info

Publication number
CN115965460A
CN115965460A CN202211463578.1A CN202211463578A CN115965460A CN 115965460 A CN115965460 A CN 115965460A CN 202211463578 A CN202211463578 A CN 202211463578A CN 115965460 A CN115965460 A CN 115965460A
Authority
CN
China
Prior art keywords
grid
grid area
area
preset
user
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202211463578.1A
Other languages
Chinese (zh)
Other versions
CN115965460B (en
Inventor
鲁健翔
唐海会
薛海伟
戴小村
谭红
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hunan Changyin May 8th Consumer Finance Co ltd
Original Assignee
Hunan Changyin May 8th Consumer Finance Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hunan Changyin May 8th Consumer Finance Co ltd filed Critical Hunan Changyin May 8th Consumer Finance Co ltd
Priority to CN202211463578.1A priority Critical patent/CN115965460B/en
Publication of CN115965460A publication Critical patent/CN115965460A/en
Application granted granted Critical
Publication of CN115965460B publication Critical patent/CN115965460B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Landscapes

  • Alarm Systems (AREA)

Abstract

The application relates to an abnormal service identification method, an abnormal service identification device, a computer device, a storage medium and a computer program product. The method comprises the following steps: determining a grid area where a user registration position is located under different preset grid division rules; counting the number of registered users in a preset time in each grid area; identifying the grid area corresponding to the registered user number exceeding a preset user number threshold value to obtain a target grid area; and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message. According to the whole scheme, the grid area where the registered user is located is preferably located through the grid areas under various different grid division rules, the problem that the target grid area is inaccurately located due to single grid area location and further abnormal service judgment is inaccurate is solved, abnormal services are identified by counting the number of the registered users in the target grid area, and the accuracy of abnormal service identification is improved.

Description

Abnormal service identification method and device, computer equipment and storage medium
Technical Field
The present application relates to the field of big data technologies, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for identifying an abnormal transaction group.
Background
With the rapid popularization of the mobile internet, the traditional offline service is gradually transferred to the online service, and the online service is not limited by space and time, so that great convenience is brought to the life of people, and high-efficiency, convenient and high-quality service can be provided.
However, due to the lack of offline verification link, the online service transaction is easy to have fraud problem, which usually shows that a large number of users in a certain place collectively perform service registration, and taking financial services as an example, a large number of lawbreakers use information differences to collectively apply for personal financial credit products in a certain area by cheating customer information.
Therefore, a method for accurately identifying abnormal services is urgently needed in the process of handling online services.
Disclosure of Invention
In view of the foregoing, it is necessary to provide an accurate abnormal service identification method, apparatus, computer device, computer readable storage medium, and computer program product for solving the technical problem of abnormal service occurring in the service handling.
In a first aspect, the present application provides a method for identifying an abnormal service. The method comprises the following steps:
responding to the user registration operation, and determining the registration position of the registered user;
determining a grid area of the registration position under different preset grid division rules;
counting the number of registered users in each grid area within preset time;
identifying the grid area where the number of registered users exceeds a preset user number threshold value and corresponding to the registered users to obtain a target grid area;
and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message.
In one embodiment, before determining the grid region where the registration position is located under the preset different grid division rules, the method further includes: acquiring a target monitoring area and a preset grid area; dividing a target monitoring area into a plurality of first type grid areas equally according to a preset grid area by taking the boundary of the target monitoring area as an initial boundary to obtain a first grid area set; dividing a target monitoring area into a plurality of second type grid areas by taking a longitudinal central axis of the first type grid area as an initial boundary according to a preset grid area to obtain a second grid area set; and dividing the target monitoring area into a plurality of third type grid areas according to the preset grid area by taking the transverse central axis of the first type grid area as an initial boundary to obtain a third grid area set.
In one embodiment, the method further includes: dividing a target monitoring area into a plurality of fourth type grid areas by taking a transverse central axis of the second type grid area as an initial boundary according to a preset grid area to obtain a fourth grid area set; or, dividing the target monitoring area into a plurality of fourth type grid areas according to the preset grid area by taking the longitudinal central axis of the third type grid area as an initial boundary, so as to obtain a fourth grid area set.
In one embodiment, determining the grid area where the registration position is located under the preset different grid division rules includes: extracting longitude and latitude information of the registration position; and determining the grid area of the registration position under different preset grid division rules according to the latitude and longitude information.
In one embodiment, each grid region under different preset grid division rules maintains a user registration queue; the step of counting the number of registered users in each grid area within a preset time comprises the following steps: acquiring a user registration queue of each grid area within preset time; and adding the registered users into the user registration queue, and counting the number of the registered users in the updated user registration queue.
In one embodiment, the method further includes: counting the enqueue time of registered users in a user registration queue; and regularly clearing the registered users with the enqueue time exceeding a preset time threshold.
In a second aspect, the present application further provides an abnormal service identification apparatus. The device comprises:
a registration position determination module for determining a registration position of a registered user in response to a user registration operation;
the grid area determining module is used for determining the grid area of the registration position under different preset grid division rules;
the statistical module is used for counting the number of registered users in each grid area within preset time;
the identification module is used for identifying the grid area corresponding to the registered user number exceeding a preset user number threshold value to obtain a target grid area;
and the judging module is used for judging that the registered user corresponding to the target grid area triggers abnormal service operation and pushing the abnormal service early warning message.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:
responding to the user registration operation, and determining the registration position of the registered user;
determining a grid area of the registration position under different preset grid division rules;
counting the number of registered users in a preset time in each grid area;
identifying the grid area corresponding to the registered user number exceeding a preset user number threshold value to obtain a target grid area;
and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message.
In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
responding to the user registration operation, and determining the registration position of the registered user;
determining a grid area of a registration position under different preset grid division rules;
counting the number of registered users in each grid area within preset time;
identifying the grid area where the number of registered users exceeds a preset user number threshold value and corresponding to the registered users to obtain a target grid area;
and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message.
In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:
responding to the user registration operation, and determining the registration position of the registered user;
determining a grid area of the registration position under different preset grid division rules;
counting the number of registered users in each grid area within preset time;
identifying the grid area corresponding to the registered user number exceeding a preset user number threshold value to obtain a target grid area;
and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message.
The abnormal service identification method, the abnormal service identification device, the computer equipment, the storage medium and the computer program product respond to the user registration operation and determine the registration position of the registered user; determining a grid area of the registration position under different preset grid division rules; counting the number of registered users in a preset time in each grid area; identifying the grid area where the number of registered users exceeds a preset user number threshold value and corresponding to the registered users to obtain a target grid area; and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message. The registration position of the registered user is firstly determined according to the whole scheme, the grid area where the registered user is located can be accurately positioned according to the registration position, the grid area where the registered user is located is positioned through the grid areas under various different grid division rules, the problem that the abnormal service judgment is inaccurate due to inaccurate positioning of the target grid area caused by single grid area positioning is solved, then, the abnormal service is identified by counting the number of the registered users in the target grid area, and the accuracy of identifying the abnormal service is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments or the conventional technologies of the present application, the drawings used in the descriptions of the embodiments or the conventional technologies will be briefly introduced below, it is obvious that the drawings in the following descriptions are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a diagram of an exemplary application environment for a method for abnormal traffic identification;
FIG. 2 is a flow chart illustrating a method for identifying abnormal traffic in one embodiment;
FIG. 3 is a flow diagram illustrating the partitioning of grid regions in one embodiment;
FIG. 4 is a diagram illustrating various types of meshing area divisions, in one embodiment;
FIG. 5 is a flowchart illustrating a method for identifying abnormal traffic in another embodiment;
FIG. 6 is a block diagram showing the structure of an abnormal traffic recognizing apparatus according to an embodiment;
FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
It should be noted that, the user information (including but not limited to user device information, user personal information, user registration address, user registration time, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The abnormal service identification method provided by the embodiment of the application can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104, or may be located on the cloud or other network server. A user performs business operation on the terminal 102, firstly, the user needs to register to become a new user, registration information is submitted to the server 104, and the server monitors and responds to the user registration operation of the user on the terminal 102 to determine the registration position of the registered user; determining a grid area of the registration position under different preset grid division rules; counting the number of registered users in each grid area within preset time; identifying the grid area where the number of registered users exceeds a preset user number threshold value and corresponding to the registered users to obtain a target grid area; and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices and portable wearable devices, and the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart car-mounted devices, and the like. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, and the like. The server 104 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers.
In one embodiment, as shown in fig. 2, an abnormal traffic identification method is provided, which is described by taking the method as an example applied to the server 104 in fig. 1, and includes the following steps:
in response to the user registration operation, a registration location of the registered user is determined, step 202.
The user registration operation refers to a behavior that a user performs service operation through a terminal and performs user registration first. The server may be a server corresponding to the service system. The registered user refers to a user who is registered when the service system performs service operation, and the registration position refers to a registration address of a registration place where the user is registered when the service system performs registration. The registration address includes latitude and longitude information.
Specifically, when a user completes registration operation in a service system through a terminal, the terminal collects user registration information and uploads the user registration information to a server, and the server intercepts and responds to the registration operation of the user in the service system to obtain a user registration address carried in the user registration information.
And 204, determining the grid area of the registration position under different preset grid division rules.
The grid area refers to an area obtained by grid division of a target monitoring area, the target monitoring area refers to an area monitored by a business system for abnormal business, the monitoring area may include a territory area of a country, an administrative division area of a province, a land area of a city, and the like, and the monitoring area may be divided according to business monitoring requirements, which is not limited herein. Different grid division rules refer to different grid division rules aiming at the target monitoring area, and different grid division results are obtained according to the different grid division rules, namely different grid areas are obtained according to the different grid division rules. Each grid region comprises 4 grid vertexes, each grid vertex carries longitude and latitude coordinates, and further, in one grid region, each grid vertex comprises a northwest vertex, a northeast vertex, a southwest vertex and a southeast vertex, the northwest vertex is the same as the northeast vertex in latitude, the southwest vertex is the same as the southeast vertex in latitude, the northwest vertex is the same as the southwest vertex in longitude, and the northeast vertex is the same as the southeast vertex in longitude. Each grid region has a unique grid number, that is, the grid numbers of different grids are different. Each mesh region is also provided with a respective mesh type.
Specifically, the server acquires multiple types of grid area sets under different preset grid division rules, queries in each type of grid area set, determines whether a grid area to which the registration position belongs exists in each type of grid, and records the grid area if the grid area belongs. The grid area includes the grid type and the grid number.
Further, the user may have the located grid region in all of the multiple types of grid region sets, may have two or more located grid regions in all of the multiple types of grid region sets, and may have the located grid region in only one type of grid region set.
And step 206, counting the number of registered users in each grid area within a preset time.
The server distributes a user registration queue to maintain the information of the newly added users of the grid area within the preset time aiming at each grid area in each type of grid area set. The preset time refers to the enqueue time of the registered user in the newly added queue, and if the enqueue time exceeds the preset time, the registered user dequeues. The user registration queue in this embodiment may also be implemented by a new user array, a new user set, and the like, where the functions of the new user array and the new user set are the same as those of the user registration queue, and the registered users whose registration time is within the preset time are stored. In this embodiment, the example of storing the registered user in the user registration queue is explained, and other implementation principles are the same, and this embodiment is not limited herein.
Specifically, after determining a grid area where a registered user is located, the server determines a grid type and a grid number, acquires a user registration queue corresponding to the grid type and the grid number, adds the registered user into the user registration queue, and then counts the number of registered users in a preset time of the user registration queue.
Specifically, the server adds the registered user into a registered user queue of the grid area where the registered user is located, and counts the number of newly added users in the registered user queue in each grid area where the registered user is located within preset time.
And 208, identifying the grid area corresponding to the registered user number exceeding the preset user number threshold value to obtain the target grid area.
The preset user quantity threshold refers to a registered user early warning threshold of a grid area within a preset time, for example, the preset time is one day, the service system is a user loan service system, the registered user early warning threshold is 1 ten thousand, and if the registered loan users of a certain grid area exceed 1 ten thousand within one day, the grid area is identified as a target grid area.
Specifically, the number of registered users in each grid area where the registered users are located is counted, the number of registered users in each grid area within preset time is counted, and when the number of registered users in the grid area exceeds a preset user number threshold, the grid area is determined as a target grid area.
Step 210, judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message.
Specifically, the server judges that the registered user in the target grid area triggers abnormal service operation, and pushes an abnormal service early warning message to the terminal. Further, the server can also automatically notify the service administrator through a short message or other warning notification mechanisms. Taking the financial loan service as an example, when loan users in a certain area exceed a preset user quantity threshold value within a certain time, the grid area is determined as a target grid area, the target grid area is marked as a suspected fraud place, the grid area is listed as a high risk area, and then all registered users in the grid area automatically perform height monitoring.
In the abnormal service identification method, the registration position of a registered user is determined in response to user registration operation; determining a grid area of the registration position under different preset grid division rules; counting the number of registered users in each grid area within preset time; identifying the grid area where the number of registered users exceeds a preset user number threshold value and corresponding to the registered users to obtain a target grid area; and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message. The registration position of the registered user is firstly determined according to the whole scheme, the grid area where the registered user is located can be accurately positioned according to the registration position, the grid area where the registered user is located is positioned through the grid areas under various different grid division rules, the problem that the abnormal service judgment is inaccurate due to inaccurate positioning of the target grid area caused by single grid area positioning is solved, then, the abnormal service is identified by counting the number of the registered users in the target grid area, and the accuracy of identifying the abnormal service is improved.
In an optional embodiment, as shown in fig. 3, before determining the grid area where the registration position is located under the preset different grid-dividing rules, the method further includes:
step 302, a target monitoring area and a preset grid area are obtained.
The target monitoring area is a service development area. The preset grid area is the grid area of the preset grid area, the shape of the preset grid area can be a square, and can also be a rectangle and the like, and for uniform grid division, the grid area is taken as the square for explanation.
Specifically, the server acquires map information of a target monitoring area, the map comprises boundary information of the target monitoring area, the boundary information comprises boundary vertexes and longitude and latitude coordinates of the boundary vertexes, meanwhile, the terminal acquires preset grid areas, and the preset grid areas of all types of grid areas are the same.
Step 304, taking the boundary of the target monitoring area as an initial boundary, equally dividing the target monitoring area into a plurality of first type grid areas according to the preset grid area, and obtaining a first grid area set.
The data structure of the grid area comprises a grid number, four vertexes of the grid and the side length of the grid.
Grid numbering: GRID _ CODE, globally unique.
Northwest VERTEX longitude (GRID _ VERTEX _ WN _ LON), northwest VERTEX latitude (GRID _ VERTEX _ WN _ LAT), southwest VERTEX longitude (GRID _ VERTEX _ WS _ LON), southwest VERTEX latitude (GRID _ VERTEX _ WS _ LAT), northeast VERTEX longitude (GRID _ VERTEX _ EN _ LON), northwest VERTEX latitude (GRID _ VERTEX _ EN _ LAT), southeast VERTEX longitude (GRID _ VERTEX _ ES _ LON), and southeast VERTEX latitude (GRID _ VERTEX _ ES _ LAT).
Side length of the grid: SIDE _ LENGTH, SIDE LENGTH N.
The four vertices are represented by two-dimensional data [ [ J1, W1], [ J2, W2], [ J3, W3], [ J4, W4] ]
Therefore, the data table structure (T _ GRID) of all the mesh regions of the target monitoring region is as shown in table 1:
TABLE 1 data sheet structure for grid zones
Figure BDA0003956436590000091
Specifically, as shown in fig. 4, the server performs mesh division on the target monitoring region according to a preset mesh area, first, determines a boundary of the target monitoring region, then uses the boundary of the target monitoring region as an initial boundary, then divides a region with an area equal to the size of the preset mesh area from the initial boundary to obtain a mesh region, and then sequentially divides the target monitoring region into a plurality of first type mesh regions according to the preset mesh area to obtain a first mesh region set.
Further, firstly, the target monitoring area is initialized, the boundary of the south-east and the west-north of the target monitoring area is used as a boundary, the target monitoring area is taken as a country for example, the boundary of the south-most and the north-most of the map is horizontally divided according to the target monitoring area, the boundary of the west-most and the east-most of the map is vertically divided according to the boundary of the south-most and the east-most of the map, a rectangle (the rectangle is an approximate rectangle due to the fact that the map is an ellipse) produced in the intersection area is taken as an original target monitoring area, and the area is actually larger than the territory area of the country and needs to be continuously corrected.
The longitude and latitude of the top point of the grid unit are calculated according to the side length distance of the grid, and because the earth is circular, when the grid unit is divided according to the side length distance, the spherical distance is actually adopted, so the longitude and latitude of the top point are required to be obtained according to the following modes:
the east-west longitude calculation mode of 4 vertexes of the grid is that the longitude and latitude [ J2, W2] of the northeast vertex are calculated according to the following process that a certain point is taken as the northwest vertex of the grid ([ J1, W1] represents, wherein J1 represents longitude, W1 represents latitude):
the northeast vertex is at the same latitude as the northwest vertex, so the latitude of the northwest vertex is also W1. And the distance between the northeast vertex and the northwest vertex is N meters, the earth is subjected to tangent plane on the latitude, the obtained tangent plane is circular, and J2= J1+ (N/tangent plane circumference) × 360.
The process of calculating the longitude and latitude [ J3, W3] of the southwest vertex is as follows:
the southwest vertex is at the same longitude as the northwest vertex, so the longitude of the southwest vertex is J1. The southwest vertex is N meters away from the northwest vertex, W3= W1+ (N/earth pole circumference) × 360.
The process of calculating the longitude and latitude [ J4, W4] of the southeast vertex is as follows:
the southeast vertex is at the same latitude as the southwest vertex, so the latitude of the southeast vertex is W3.
The southeast vertex is in the same longitude as the northeast vertex, so longitude J2 of the southeast vertex.
And analogizing in sequence, dividing the grid areas under the original target monitoring area according to the mode, obtaining the corresponding vertex longitude and latitude, obtaining a first type grid area set, and storing the first type grid area set in a map grid table.
And finally, correcting the actual area according to the boundary line of the monitoring area. Gradually correcting the original target monitoring area according to the longitude and latitude of the Chinese boundary, only reserving the map shape in the boundary range of the monitoring area, and deleting the grid units in the non-monitoring area from the initialized grid map to obtain an accurate first grid area set.
And step 306, dividing the target monitoring area into a plurality of second type grid areas according to a preset grid area by taking the longitudinal central axis of the first type grid area as an initial boundary, so as to obtain a second grid area set.
Specifically, after obtaining the first type of grid area, the server obtains a longitudinal central axis of the first type of grid area, and divides the target monitoring area into a plurality of second type of grid areas with the longitudinal central axis of the first type of grid area as an initial boundary, so as to obtain a second grid area set.
Furthermore, the vertex of the first type of mesh area is moved to the east by a distance of N/2 (i.e. half of the side length of the mesh) and then used as the starting point of the second type of mesh area, and the latitude and longitude of the other three vertices of the second type of mesh area are calculated according to the above mode. And repeating the rest grid areas to obtain the longitude and latitude information of all grid unit vertexes of the second type grid area so as to obtain a second grid area set.
And 308, dividing the target monitoring area into a plurality of third-type grid areas according to the preset grid area by taking the transverse central axis of the first-type grid area as an initial boundary to obtain a third grid area set.
Specifically, after obtaining the first type of grid area, the server obtains a horizontal central axis of the first type of grid area, and divides the target monitoring area into a plurality of third type of grid areas with the horizontal central axis of the first type of grid area as an initial boundary, so as to obtain a third grid area set.
Furthermore, the vertex of the first type grid area is moved to the north by a distance of N/2 to be used as a northwest vertex of the third type grid area, and the longitude and latitude of the other three vertexes of the third type grid area are calculated according to the mode. And the rest grid areas are analogized in sequence to obtain the longitude and latitude information of all grid unit vertexes of the third type grid area, so as to obtain a third grid area set.
In an optional embodiment, the method further includes: dividing a target monitoring area into a plurality of fourth type grid areas by taking a transverse central axis of the second type grid area as an initial boundary according to a preset grid area to obtain a fourth grid area set; or, dividing the target monitoring area into a plurality of fourth type grid areas according to the preset grid area by taking the longitudinal central axis of the third type grid area as an initial boundary, so as to obtain a fourth grid area set.
Specifically, after obtaining the second-type grid region, the server obtains a horizontal central axis of the second-type grid region, and divides the target monitoring region into a plurality of fourth-type grid regions by using the horizontal central axis of the second-type grid region as a starting boundary, so as to obtain a fourth grid region set.
Or after the server obtains the second type grid area, the server obtains a longitudinal central axis of the second type grid area, and divides the target monitoring area into a plurality of fourth type grid areas by taking the longitudinal central axis of the second type grid area as a starting boundary, so as to obtain a fourth grid area set.
In the embodiment, the fourth type grid area is generated in two ways based on the second type grid area, the target monitoring area is divided by the multiple types of grid areas, multiple types of grid areas can be obtained, the number of the grid areas where the registered user is located is counted based on the multiple types of grid areas, more accurate grid area results can be obtained, and more accurate abnormal service identification can be performed based on the accurate grid areas.
In an optional embodiment, determining the grid area where the registration position is located under the preset different grid division rules includes: extracting longitude and latitude information of the registration position; and determining the grid area of the registration position under different preset grid division rules according to the latitude and longitude information.
Specifically, since there are four types of grid regions, taking a target monitoring region as china for example, if a service is developed nationwide, a map of china needs to be subjected to grid initialization, that is, about 960 ten thousand square kilometers are subjected to grid processing according to a rated side length, and grids are divided according to the side length of 100 meters, so that the number of grids reaches about 9600 ten thousand; and analogize that if the business is carried out in a certain administrative region, the grid initialization is carried out only in the administrative region.
If the target monitoring area is China, about 9600 ten thousand grid areas exist, and a distributed processing mode is adopted for providing processing efficiency. The abnormal service identification processes in different types of grid areas are respectively deployed in a plurality of devices, each device identifies user registration data in all grids in the type of grid area, and registered users are collected into corresponding grids according to registration positions.
Further, the server firstly acquires the registration position from the user registration information, extracts the longitude and latitude coordinates of the registration position, then calls the distributed threads, determines the grid area where the registration position of the registered user is located through the threads of different types of grid areas and the longitude and latitude information, and obtains the grid area where the registration position of the registered user is located under different preset grid division rules.
Acquiring various grid region sets under various grid division rules; and determining the grid area of the registration position in the various grid area sets according to the latitude and longitude information. Furthermore, the server firstly collects various grid areas under various grid division rules, then searches longitude and latitude coordinates of the registered user in the various grid area collections, and quickly and accurately determines the grid area of the registered user in the various grid area collections.
In the embodiment, the grid area can be quickly determined according to the longitude and latitude coordinates of the registered user, so that the grid area determining efficiency is improved, and the abnormal service identification efficiency is further improved.
Further, each new user is registered, the registration position (longitude J0 and latitude W0) of the registered user is distributed to 4 threads, and the 4 threads compare the registration position with the grid area range processed by the current thread and gather the registration position into the corresponding grid area to obtain the grid area where the registered user is located.
The GRID units of four regions in the table T _ GRID are initialized, and since 2 vertexes on the north side of the GRID unit are on the same latitude, the GRID unit can take the latitude of the 2 vertexes on the north side, and the like, and the GRID unit is obtained according to the method for the south latitude, the west longitude and the east longitude.
The grid cell north latitude values are: GRID north VERTEX latitude (GRID _ VERTEX _ WN _ LAT),
grid cell south latitude values are: GRID south VERTEX latitude (GRID _ version _ WS _ LAT),
grid cell east longitude values are: GRID east VERTEX longitude (GRID _ VERTEX _ EN _ LON),
the grid cell west longitude values are: GRID east VERTEX longitude (GRID _ VERTEX _ WN _ LON).
Then, in the thread of each type of grid area, judging that the current item forward point belongs to the grid area through SQL, taking China as an example of a target monitoring area, wherein the target monitoring area belongs to the northeast hemisphere, the longitude is from west to east, and the numerical value is increased; the latitude changes from north to south, and the number decreases.
Sql1:Select*From T_GRID where J0>=GRID_VERTEX_WN_LON And J0<=GRID_VERTEX_EN_LON And W0<=GRID_VERTEX_WN_LAT And WO>=GRID_VERTEX_WS_LAT;
Then, there may be multiple records in the obtained record, that is, the grid area where the registered user is present, which indicates that the registered position of the registered user is on the grid edge and belongs to multiple grid areas.
If the grid area is divided according to only one rule, registered users gathered at the edges of two adjacent grids or a plurality of grids can not be counted in one grid, and the statistics are incomplete. For example, if the grid areas are divided according to the first type, clusters are generated at the edges of adjacent grids, such as two registered users of the second type grid area in the figure, which are respectively counted in the first type a and B grids, but actually gather in the second type grid area, and thus if the grid areas are divided according to only a single type, the statistics are incomplete. Because the abnormal business identification is mainly carried out, whether the risk of part feeding and gathering exists is counted, the early warning is not influenced by repeated counting, and a more accurate identification result can be obtained.
In an optional embodiment, each grid region under different preset grid division rules maintains a user registration queue; the step of counting the number of registered users in each grid region within a preset time comprises the following steps: acquiring a user registration queue of each grid area within preset time; and adding the registered users into the user registration queue, and counting the number of the registered users in the updated user registration queue.
The user registration queue includes a structure of each user including a grid number, a longitude, a latitude, and registration time, as shown in table 2 below:
TABLE 2 user registration queue List
Name of field Type of field Meaning of a field Remarks for note
GRID_CODE Varchar(32) Trellis coding
APPLY_GPS_LON BigDecimal(10,7) Register longitude
APPLY_GPS_LAT BigDecimal(10,7) Registration latitude
APPLY_TIME Timestamp Registration time
Specifically, the server determines GRID number GRID _ CODE (G1) of a GRID area where the registered user is located, and longitude and latitude of a registration position, and registration time are written into a user registration queue (T _ application). And acquiring a user registration queue of each grid region in a preset time, adding registered users into the user registration queue, and counting the number of the registered users in the updated user registration queue.
And triggering an early warning statistical function every time 1 registered user is added, wherein the early warning statistical function is mainly used for counting the event-entering point under the grid cell within a preset time (duration _ time) through sql2 according to the fact that the registered user belongs to the grid cell code.
Sql2:Select count(1)from T_APPLY where GRID_CODE=G1 and apply_time>=now()+duration_time。
In the embodiment, the number of registered users in each grid area is counted through the user registration queue, the number of users in the queue is simply and efficiently determined, and then abnormal service identification is rapidly carried out. In addition, a service white list can be set in the server, and the user in the service white list carries the identifier. Because the online outlet can have a registered user list for transacting the service offline through service personnel, the operation of importing the online registered users in batch is carried out, the service personnel can import the registered user list for identification, and when the server detects that the registered user carries the identification, the user carrying the identification is not added into the user registration queue, so that the identification efficiency of the abnormal service is improved.
In an optional embodiment, the method further includes: counting the enqueuing time of a registered user in a user registration queue; and regularly clearing the registered users with the enqueue time exceeding a preset time threshold.
Specifically, the server counts the enqueue time of registered users in the user registration queue, may set a timing task, and periodically clears expired registered user data in the user registration queue of the grid area from the T _ application table according to a preset time.
In the embodiment, the registered users which are not in the preset time in the user registration queue are cleared regularly, so that the database pressure is reduced, and the abnormal service identification efficiency is improved.
In order to easily understand the technical solution provided by the embodiment of the present application, as shown in fig. 5, a complete abnormal service identification process is used to briefly describe the abnormal service identification method provided by the embodiment of the present application:
(1) And acquiring a target monitoring area and a preset grid area.
(2) And equally dividing the target monitoring area into a plurality of first type grid areas according to a preset grid area by taking the boundary of the target monitoring area as an initial boundary to obtain a first grid area set.
(3) And dividing the target monitoring area into a plurality of second type grid areas according to the preset grid area by taking the longitudinal central axis of the first type grid area as an initial boundary to obtain a second grid area set.
(4) And dividing the target monitoring area into a plurality of third type grid areas according to the preset grid area by taking the transverse central axis of the first type grid area as an initial boundary to obtain a third grid area set.
(5) Dividing a target monitoring area into a plurality of fourth type grid areas by taking a transverse central axis of the second type grid area as an initial boundary according to a preset grid area to obtain a fourth grid area set; or, dividing the target monitoring area into a plurality of fourth type grid areas according to the preset grid area by taking the longitudinal central axis of the third type grid area as an initial boundary, so as to obtain a fourth grid area set.
(6) And responding to the user registration operation, determining the registration position of the registered user, and extracting the latitude and longitude information of the registration position.
(7) Acquiring various grid region sets under various grid division rules; and determining the grid area of the registration position in the various grid area sets according to the latitude and longitude information.
(8) Acquiring a user registration queue of each grid area within preset time; and adding the registered users into the user registration queue, and counting the number of the registered users in the updated user registration queue.
(9) And identifying the grid area corresponding to the registered user number exceeding the preset user number threshold value to obtain a target grid area.
(10) And judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message.
(11) Counting the enqueue time of registered users in a user registration queue; and regularly clearing the registered users with the enqueue time exceeding a preset time threshold.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.
Based on the same inventive concept, the embodiment of the present application further provides an abnormal service identification apparatus for implementing the above-mentioned abnormal service identification method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more embodiments of the abnormal service identification device provided below can be referred to the limitations of the abnormal service identification method in the above, and details are not described here.
In one embodiment, as shown in fig. 6, there is provided an abnormal traffic identification apparatus, including: a registration location determination module 602, a grid region determination module 604, a statistics module 606, an identification module 608, and a decision module 610, wherein:
a registration location determination module 602, configured to determine a registration location of a registered user in response to a user registration operation;
a grid area determining module 604, configured to determine a grid area where the registration location is located under different preset grid division rules;
a counting module 606, configured to count the number of registered users in a preset time in each grid area;
the identifying module 608 is configured to identify a grid area where the number of registered users exceeds a preset user number threshold, to obtain a target grid area;
the determining module 610 is configured to determine that a registered user corresponding to the target grid area triggers an abnormal service operation, and push an abnormal service early warning message.
In one embodiment, the abnormal service identification apparatus further includes a dividing module, configured to obtain a target monitoring area and a preset grid area; dividing a target monitoring area into a plurality of first type grid areas equally according to a preset grid area by taking the boundary of the target monitoring area as an initial boundary to obtain a first grid area set; dividing a target monitoring area into a plurality of second type grid areas by taking a longitudinal central axis of a first type grid area as an initial boundary according to a preset grid area to obtain a second grid area set; and dividing the target monitoring area into a plurality of third type grid areas according to the preset grid area by taking the transverse central axis of the first type grid area as an initial boundary to obtain a third grid area set.
In one embodiment, the dividing module is further configured to divide the target monitoring area into a plurality of fourth type grid areas according to a preset grid area by using a horizontal central axis of the second type grid area as an initial boundary, so as to obtain a fourth grid area set; or, dividing the target monitoring area into a plurality of fourth type grid areas according to the preset grid area by taking the longitudinal central axis of the third type grid area as an initial boundary, so as to obtain a fourth grid area set.
In one embodiment, the grid region determination module 604 is further configured to extract latitude and longitude information of the registered location; and determining the grid area of the registration position under different preset grid division rules according to the latitude and longitude information.
In one embodiment, each grid region under different preset grid division rules maintains a user registration queue; the statistical module 606 is further configured to obtain a user registration queue of each grid region within a preset time; and adding the registered users into the user registration queue, and counting the number of the registered users in the updated user registration queue.
In one embodiment, the statistics module 606 is further configured to count the enqueue time of the registered user in the user registration queue; and regularly clearing the registered users with the enqueue time exceeding a preset time threshold.
All or part of each module in the abnormal service identification device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure thereof may be as shown in fig. 7. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The database of the computer device is used to store grid area collection data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement an abnormal traffic identification method.
Those skilled in the art will appreciate that the architecture shown in fig. 7 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.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
determining a registration position of a registered user in response to a user registration operation;
determining a grid area of the registration position under different preset grid division rules;
counting the number of registered users in a preset time in each grid area;
identifying the grid area where the number of registered users exceeds a preset user number threshold value and corresponding to the registered users to obtain a target grid area;
and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message.
In one embodiment, the processor when executing the computer program further performs the steps of: before determining the grid area where the registration position is located under the preset different grid division rules, the method further includes: acquiring a target monitoring area and a preset grid area; dividing a target monitoring area into a plurality of first type grid areas equally according to a preset grid area by taking the boundary of the target monitoring area as an initial boundary to obtain a first grid area set; dividing a target monitoring area into a plurality of second type grid areas by taking a longitudinal central axis of the first type grid area as an initial boundary according to a preset grid area to obtain a second grid area set; and dividing the target monitoring area into a plurality of third type grid areas according to the preset grid area by taking the transverse central axis of the first type grid area as an initial boundary to obtain a third grid area set.
In one embodiment, the processor when executing the computer program further performs the steps of: dividing a target monitoring area into a plurality of fourth type grid areas by taking a transverse central axis of the second type grid area as an initial boundary according to a preset grid area to obtain a fourth grid area set; or, dividing the target monitoring area into a plurality of fourth type grid areas according to the preset grid area by taking the longitudinal central axis of the third type grid area as an initial boundary, so as to obtain a fourth grid area set.
In one embodiment, the processor, when executing the computer program, further performs the steps of: determining the grid area of the registration position under the preset different grid division rules comprises: extracting longitude and latitude information of the registered position; and determining the grid area of the registration position under different preset grid division rules according to the latitude and longitude information.
In one embodiment, the processor, when executing the computer program, further performs the steps of: maintaining a user registration queue in each grid region under different preset grid division rules; the step of counting the number of registered users in each grid area within a preset time comprises the following steps: acquiring a user registration queue of each grid area in a preset time; and adding the registered users into the user registration queue, and counting the number of the registered users in the updated user registration queue.
In one embodiment, the processor when executing the computer program further performs the steps of: counting the enqueuing time of a registered user in a user registration queue; and regularly clearing the registered users with the enqueue time exceeding a preset time threshold.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
responding to the user registration operation, and determining the registration position of the registered user;
determining a grid area of the registration position under different preset grid division rules;
counting the number of registered users in each grid area within preset time;
identifying the grid area corresponding to the registered user number exceeding a preset user number threshold value to obtain a target grid area;
and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message.
In one embodiment, the computer program when executed by the processor further performs the steps of: before determining the grid area where the registration position is located under different preset grid division rules, the method further includes: acquiring a target monitoring area and a preset grid area; dividing a target monitoring area into a plurality of first type grid areas equally according to a preset grid area by taking the boundary of the target monitoring area as an initial boundary to obtain a first grid area set; dividing a target monitoring area into a plurality of second type grid areas by taking a longitudinal central axis of the first type grid area as an initial boundary according to a preset grid area to obtain a second grid area set; and dividing the target monitoring area into a plurality of third type grid areas according to the preset grid area by taking the transverse central axis of the first type grid area as an initial boundary to obtain a third grid area set.
In one embodiment, the computer program when executed by the processor further performs the steps of: dividing a target monitoring area into a plurality of fourth type grid areas by taking a transverse central axis of the second type grid area as an initial boundary according to a preset grid area to obtain a fourth grid area set; or, dividing the target monitoring area into a plurality of fourth type grid areas according to the preset grid area by taking the longitudinal central axis of the third type grid area as an initial boundary, so as to obtain a fourth grid area set.
In one embodiment, the computer program when executed by the processor further performs the steps of: determining the grid area of the registration position under the preset different grid division rules comprises: extracting longitude and latitude information of the registered position; and determining the grid area of the registration position under different preset grid division rules according to the latitude and longitude information.
In one embodiment, the computer program when executed by the processor further performs the steps of: maintaining a user registration queue in each grid region under different preset grid division rules; the step of counting the number of registered users in each grid area within a preset time comprises the following steps: acquiring a user registration queue of each grid area within preset time; and adding the registered users into the user registration queue, and counting the number of the registered users in the updated user registration queue.
In one embodiment, the computer program when executed by the processor further performs the steps of: counting the enqueue time of registered users in a user registration queue; and regularly clearing the registered users with the enqueue time exceeding a preset time threshold.
In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the steps of:
determining a registration position of a registered user in response to a user registration operation;
determining a grid area of the registration position under different preset grid division rules;
counting the number of registered users in a preset time in each grid area;
identifying the grid area corresponding to the registered user number exceeding a preset user number threshold value to obtain a target grid area;
and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message.
In one embodiment, the computer program when executed by the processor further performs the steps of: before determining the grid area where the registration position is located under the preset different grid division rules, the method further includes: acquiring a target monitoring area and a preset grid area; dividing a target monitoring area into a plurality of first type grid areas equally according to a preset grid area by taking the boundary of the target monitoring area as an initial boundary to obtain a first grid area set; dividing a target monitoring area into a plurality of second type grid areas by taking a longitudinal central axis of the first type grid area as an initial boundary according to a preset grid area to obtain a second grid area set; and dividing the target monitoring area into a plurality of third type grid areas according to the preset grid area by taking the transverse central axis of the first type grid area as an initial boundary to obtain a third grid area set.
In one embodiment, the computer program when executed by the processor further performs the steps of: dividing a target monitoring area into a plurality of fourth type grid areas by taking a transverse central axis of the second type grid area as an initial boundary according to a preset grid area to obtain a fourth grid area set; or, dividing the target monitoring area into a plurality of fourth type grid areas according to the preset grid area by taking the longitudinal central axis of the third type grid area as an initial boundary, so as to obtain a fourth grid area set.
In one embodiment, the computer program when executed by the processor further performs the steps of: determining the grid area of the registration position under different preset grid division rules comprises the following steps: extracting longitude and latitude information of the registered position; and determining the grid area of the registration position under different preset grid division rules according to the latitude and longitude information.
In one embodiment, the computer program when executed by the processor further performs the steps of: maintaining a user registration queue in each grid region under different preset grid division rules; the step of counting the number of registered users in each grid region within a preset time comprises the following steps: acquiring a user registration queue of each grid area within preset time; and adding the registered users into the user registration queue, and counting the number of the registered users in the updated user registration queue.
In one embodiment, the computer program when executed by the processor further performs the steps of: counting the enqueue time of registered users in a user registration queue; and regularly clearing the registered users with the enqueue time exceeding a preset time threshold.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), magnetic Random Access Memory (MRAM), ferroelectric Random Access Memory (FRAM), phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims (10)

1. An abnormal service identification method, characterized in that the method comprises:
determining a registration position of a registered user in response to a user registration operation;
determining the grid area of the registration position under different preset grid division rules;
counting the number of registered users in each grid area within preset time;
identifying the grid area corresponding to the registered user number exceeding a preset user number threshold value to obtain a target grid area;
and judging that the registered user corresponding to the target grid area triggers abnormal service operation, and pushing an abnormal service early warning message.
2. The method according to claim 1, wherein said determining the grid area where the registration location is located under different preset grid-dividing rules further comprises:
acquiring a target monitoring area and a preset grid area;
equally dividing the target monitoring area into a plurality of first type grid areas according to the preset grid area by taking the target monitoring area boundary as an initial boundary to obtain a first grid area set;
dividing the target monitoring area into a plurality of second type grid areas according to the preset grid area by taking a longitudinal central axis of the first type grid area as an initial boundary to obtain a second grid area set;
and dividing the target monitoring area into a plurality of third type grid areas according to the preset grid area by taking the transverse central axis of the first type grid area as an initial boundary to obtain a third grid area set.
3. The method of claim 2, further comprising:
dividing the target monitoring area into a plurality of fourth type grid areas according to the preset grid area by taking the transverse central axis of the second type grid area as an initial boundary to obtain a fourth grid area set;
or, dividing the target monitoring area into a plurality of fourth type grid areas according to the preset grid area by taking the longitudinal central axis of the third type grid area as an initial boundary, so as to obtain a fourth grid area set.
4. The method of claim 1, wherein the determining the grid area where the registration location is located under different preset grid-division rules comprises:
extracting longitude and latitude information of the registration position;
and determining the grid area of the registration position under different preset grid division rules according to the longitude and latitude information.
5. The method according to claim 1, wherein each grid region under the preset different grid partition rules maintains a user registration queue;
the counting of the number of registered users in each grid region in a preset time includes:
acquiring a user registration queue of each grid area in a preset time;
and adding the registered user into the user registration queue, and counting the number of the updated registered users in the user registration queue.
6. The method of claim 5, further comprising:
counting the enqueuing time of the registered user in the user registration queue;
and regularly clearing the registered users with the enqueue time exceeding a preset time threshold.
7. An abnormal traffic recognition apparatus, characterized in that the apparatus comprises:
a registration position determination module for determining a registration position of a registered user in response to a user registration operation;
the grid area determining module is used for determining the grid area of the registration position under different preset grid division rules;
the statistical module is used for counting the number of registered users in each grid area within preset time;
the identification module is used for identifying the grid area corresponding to the registered user number exceeding a preset user number threshold value to obtain a target grid area;
and the judging module is used for judging that the registered user corresponding to the target grid area triggers abnormal service operation and pushing an abnormal service early warning message.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, realizes the steps of the method of any one of claims 1 to 6.
CN202211463578.1A 2022-11-22 2022-11-22 Abnormal service identification method, device, computer equipment and storage medium Active CN115965460B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202211463578.1A CN115965460B (en) 2022-11-22 2022-11-22 Abnormal service identification method, device, computer equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202211463578.1A CN115965460B (en) 2022-11-22 2022-11-22 Abnormal service identification method, device, computer equipment and storage medium

Publications (2)

Publication Number Publication Date
CN115965460A true CN115965460A (en) 2023-04-14
CN115965460B CN115965460B (en) 2023-09-01

Family

ID=87358788

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202211463578.1A Active CN115965460B (en) 2022-11-22 2022-11-22 Abnormal service identification method, device, computer equipment and storage medium

Country Status (1)

Country Link
CN (1) CN115965460B (en)

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105808988A (en) * 2014-12-31 2016-07-27 阿里巴巴集团控股有限公司 Method and device for identifying exceptional account
CN106339615A (en) * 2016-08-29 2017-01-18 北京红马传媒文化发展有限公司 Abnormal registration behavior recognition method, system and equipment
CN108513301A (en) * 2017-02-23 2018-09-07 中国移动通信有限公司研究院 A kind of disabled user's recognition methods and device
CN109657146A (en) * 2018-12-21 2019-04-19 拉扎斯网络科技(上海)有限公司 Distributed search method, device and system, main server and regional server
CN110222964A (en) * 2019-05-28 2019-09-10 阿里巴巴集团控股有限公司 A kind of user account risk prevention system method, system and electronic equipment
CN111556059A (en) * 2020-04-29 2020-08-18 深圳壹账通智能科技有限公司 Abnormity detection method, abnormity detection device and terminal equipment
CN111835561A (en) * 2020-06-29 2020-10-27 中国平安财产保险股份有限公司 Abnormal user group detection method, device and equipment based on user behavior data
CN112613893A (en) * 2020-12-28 2021-04-06 杭州拼便宜网络科技有限公司 Method, system, equipment and medium for identifying malicious user registration
CN114429355A (en) * 2022-01-28 2022-05-03 杭州网易智企科技有限公司 Method, device, medium and equipment for generating identification characteristics of abnormal registration event

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105808988A (en) * 2014-12-31 2016-07-27 阿里巴巴集团控股有限公司 Method and device for identifying exceptional account
CN106339615A (en) * 2016-08-29 2017-01-18 北京红马传媒文化发展有限公司 Abnormal registration behavior recognition method, system and equipment
CN108513301A (en) * 2017-02-23 2018-09-07 中国移动通信有限公司研究院 A kind of disabled user's recognition methods and device
CN109657146A (en) * 2018-12-21 2019-04-19 拉扎斯网络科技(上海)有限公司 Distributed search method, device and system, main server and regional server
CN110222964A (en) * 2019-05-28 2019-09-10 阿里巴巴集团控股有限公司 A kind of user account risk prevention system method, system and electronic equipment
CN111556059A (en) * 2020-04-29 2020-08-18 深圳壹账通智能科技有限公司 Abnormity detection method, abnormity detection device and terminal equipment
CN111835561A (en) * 2020-06-29 2020-10-27 中国平安财产保险股份有限公司 Abnormal user group detection method, device and equipment based on user behavior data
CN112613893A (en) * 2020-12-28 2021-04-06 杭州拼便宜网络科技有限公司 Method, system, equipment and medium for identifying malicious user registration
CN114429355A (en) * 2022-01-28 2022-05-03 杭州网易智企科技有限公司 Method, device, medium and equipment for generating identification characteristics of abnormal registration event

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
付守欢: ""大数据时代银行账户风险防范措施研究"", 《现代金融》, no. 07, pages 49 - 51 *

Also Published As

Publication number Publication date
CN115965460B (en) 2023-09-01

Similar Documents

Publication Publication Date Title
US20190197570A1 (en) Location-based analytic platform and methods
US20200118075A1 (en) Method and apparatus for dividing delivery regions, electronic device, and computer-readable storage medium
Sisk et al. Identifying extinction threats
EP3032780B1 (en) Method and apparatus for transmitting messages to users using trajectory-based clustering
CN104200369B (en) Method and device for determining commodity distribution range
US20180096253A1 (en) Rare event forecasting system and method
WO2016188380A1 (en) Determination method and apparatus for user equipment
CN110347888B (en) Order data processing method and device and storage medium
CN110569321A (en) grid division processing method and device based on urban map and computer equipment
Bao et al. Heterogeneity issues in local measurements of spatial association
US20180173801A1 (en) Method and apparatus for processing online user distribution
CN111709661A (en) Risk processing method, device and equipment for business data and storage medium
CN114265740A (en) Error information processing method, device, equipment and storage medium
CN112860808A (en) User portrait analysis method, device, medium and equipment based on data tag
CN114495137A (en) Bill abnormity detection model generation method and bill abnormity detection method
CN115965460B (en) Abnormal service identification method, device, computer equipment and storage medium
EP4238322A1 (en) Method for allocating resources in a geographic area
CN106156122B (en) Transaction information acquisition method and device
CN110737673A (en) data processing method and system
CN112100177A (en) Data storage method and device, computer equipment and storage medium
CN116681298A (en) Wind farm location method, wind farm location device, computer equipment, storage medium and product
CN115293809A (en) Typhoon and rainstorm risk rating method based on artificial intelligence and related equipment
CN115879819A (en) Enterprise credit evaluation method and device
CN116401238A (en) Deviation monitoring method, apparatus, device, storage medium and program product
CN109544304B (en) Method for carrying out early warning according to mobile terminal information

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant