User identity authentication method and device

Abstract

The invention provides a user identity authentication method and device, which can be used in the technical field of information security and financial science and technology, and the method comprises the following steps: collecting historical operation position data of a user on each page of a mobile banking, and obtaining a sliding distance data set according to the historical operation position data, historical sliding distance data of the user on each page is recorded in the sliding distance data set; according to the feature information of each page, carrying out clustering calculation on historical sliding distance data of the user on each page in the sliding distance data set, and determining a sliding distance data range of each page according with user features; the pages with the historical operation times larger than the mean value of the historical operation times of all the pages are screened out to serve as pages needing to monitor user behaviors; and acquiring sliding distance data of the user on the page of which the user behavior needs to be monitored, comparing the sliding distance data of the user on the page with the sliding distance data range of the page according with the user characteristics, and determining whether the user operates on the page or not.

Description

Technical Field

[0001] The present invention relates to the technical field of information security and financial technology, and in particular to a user identity authentication method and device. Background Art

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

[0003] At present, the banking industry's methods for user authentication are mostly concentrated in the field of media authentication. For example, user identity verification is performed through single or multiple authentications of static media such as passwords, fingerprints, and faces, thereby completing user identity authentication and confirming user identity for terminal login, business processing, and other matters; however, static media such as passwords, fingerprints, and faces are easily recorded by criminals, thereby affecting the security of client business operations. Summary of the invention

[0004] In an embodiment of the present invention, a user identity authentication method is proposed to confirm whether the operator is the user himself, thereby improving the security of client business operations, including:

[0005] Collect the historical operation location data of users on each page of mobile banking, and obtain the sliding distance data set based on the historical operation location data. The sliding distance data set records the historical sliding distance data of users on each page;

[0006] According to the characteristic information of each page, cluster calculation is performed on the historical sliding distance data of users on each page in the sliding distance data set to determine the sliding distance data range of each page that meets the user characteristics;

[0007] Determine the historical operation times of the user on each page, and select the pages whose historical operation times are greater than the average of the historical operation times of each page as the pages that need to monitor user behavior;

[0008] When a user operation occurs on a page whose user behavior needs to be monitored, the sliding distance data of the user on the page is obtained, and according to the characteristic information of the page, the sliding distance data of the user on the page is compared with the sliding distance data range of the page that meets the user characteristics;

[0009] If the user's sliding distance data on the page falls within the sliding distance data range that matches the user's characteristics, it is confirmed that the user himself operated on the page; otherwise, it is confirmed as a risk event and the user is notified.

[0010] In an embodiment of the present invention, a user identity authentication device is proposed to confirm whether the operator is the user himself, thereby improving the security of client business operations, including:

[0011] The data collection module is used to collect the historical operation location data of the user on each page of the mobile banking, and obtain the sliding distance data set according to the historical operation location data. The sliding distance data set records the historical sliding distance data of the user on each page;

[0012] The clustering calculation module is used to perform clustering calculation on the historical sliding distance data of the user on each page in the sliding distance data set according to the characteristic information of each page, and determine the sliding distance data range of each page that meets the user characteristics;

[0013] The page screening module is used to determine the number of historical operations of the user on each page, and screen out pages whose number of historical operations is greater than the average number of historical operations of each page as pages that need to monitor user behavior;

[0014] A data comparison module is used to obtain the sliding distance data of the user on the page when a user operation occurs on the page where the user behavior needs to be monitored, and compare the sliding distance data of the user on the page with the sliding distance data range of the page that meets the user characteristics according to the characteristic information of the page;

[0015] The operation judgment module is used to confirm that the user has operated on the page if the sliding distance data of the user on the page falls within the sliding distance data range that meets the user's characteristics; otherwise, it is confirmed as a risk event and notifies the user himself.

[0016] In an embodiment of the present invention, a computer device is proposed, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements a user identity authentication method when executing the computer program.

[0017] In an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, a user identity authentication method is implemented.

[0018] The user identity authentication method and device proposed in the embodiment of the present invention can solve the problem in the prior art that static media such as passwords, fingerprints, and faces are easily recorded by criminals, thereby affecting the security of business operations; the embodiment of the present invention collects historical operation position data of users on various pages of mobile banking, obtains a sliding distance data set according to the historical operation position data, and records the historical sliding distance data of users on various pages in the sliding distance data set; according to the characteristic information of each page, cluster calculation is performed on the historical sliding distance data of users on various pages in the sliding distance data set to determine the sliding distance data range of each page that meets the user characteristics; the number of historical operations of users on each page is determined, and pages with historical operation times greater than the average number of historical operation times of each page are screened out as pages that need to monitor user behavior; when a user operation occurs on a page that needs to monitor user behavior, the sliding distance data of the user on the page is obtained, and according to the characteristic information of the page, the sliding distance data of the user on the page is compared with the sliding distance data range of the page that meets the user characteristics; if the sliding distance data of the user on the page falls into the sliding distance data range that meets the user characteristics of the page, it is confirmed that the user himself operates on the page; otherwise, it is confirmed as a risk event and the user himself is notified. The embodiment of the present invention can confirm whether the operator is the user himself by the sliding distance of the user on the mobile banking page, thereby improving the security of client business operations; in addition, the pages that need to monitor user behavior are screened out, and there is no need to monitor every page, which can reduce the pressure on the back-end server. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 is a flowchart of a user identity authentication method in an embodiment of the present invention;

[0021] Figure 2 is a specific example diagram of the user identity authentication method in an embodiment of the present invention;

[0022] Figure 3 is a specific example diagram of the user identity authentication method in an embodiment of the present invention;

[0023] Figure 4 is a specific example diagram of the user identity authentication method in an embodiment of the present invention;

[0024] Figure 5 is a schematic diagram of a user identity authentication device in an embodiment of the present invention;

[0025] Figure 6 Schematic diagram of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0026] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0027] The term "and / or" herein only describes an association relationship, indicating that three relationships may exist. For example, A and / or B may represent the following three situations: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C may represent including any one or more elements selected from the set consisting of A, B, and C.

[0028] In the description of this specification, the terms "include", "including", "have", "contain", etc. are all open terms, which mean including but not limited to. The descriptions with reference to the terms "one embodiment", "a specific embodiment", "some embodiments", "for example", etc. mean that the specific features, structures or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. The order of steps involved in each embodiment is used to schematically illustrate the implementation of the present application, and the order of steps is not limited and can be appropriately adjusted as needed.

[0029] The principle and spirit of the present invention are explained in detail below with reference to several representative embodiments of the present invention.

[0030] Figure 1 FIG. 1 is a flow chart of a user identity authentication method according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0031] Step 101, collecting historical operation location data of the user on each page of the mobile banking, obtaining a sliding distance data set according to the historical operation location data, and recording the historical sliding distance data of the user on each page in the sliding distance data set;

[0032] Step 102, based on the characteristic information of each page, cluster calculation is performed on the historical sliding distance data of the user on each page in the sliding distance data set to determine the sliding distance data range of each page that meets the user characteristics;

[0033] Step 103, determining the number of historical operations of the user on each page, and selecting pages whose number of historical operations is greater than the average number of historical operations of each page as pages that need to monitor user behavior;

[0034] Step 104, when a user operation occurs on a page whose user behavior needs to be monitored, the sliding distance data of the user on the page is obtained, and according to the characteristic information of the page, the sliding distance data of the user on the page is compared with the sliding distance data range of the page that meets the user characteristics;

[0035] Step 105, if the sliding distance data of the user on the page falls within the sliding distance data range of the page that meets the user's characteristics, it is confirmed that the user himself operates on the page; otherwise, it is confirmed as a risk event and the user is notified.

[0036] Depend on Figure 1 It can be seen from the illustrated process that the embodiment of the present invention collects historical operation position data of users on various pages of mobile banking, obtains a sliding distance data set based on the historical operation position data, and records the historical sliding distance data of users on various pages in the sliding distance data set; according to the characteristic information of each page, cluster calculation is performed on the historical sliding distance data of users on various pages in the sliding distance data set to determine the sliding distance data range that meets the user characteristics of each page; the number of historical operations of users on each page is determined, and pages whose historical operation times are greater than the average number of historical operations of each page are screened out as pages that require user behavior monitoring; when a user operation occurs on a page that requires user behavior monitoring, the sliding distance data of the user on the page is obtained, and according to the characteristic information of the page, the sliding distance data of the user on the page is compared with the sliding distance data range that meets the user characteristics of the page; if the sliding distance data of the user on the page falls within the sliding distance data range that meets the user characteristics of the page, it is confirmed that the user himself has operated on the page; otherwise, it is confirmed as a risk event and the user himself is notified. The embodiment of the present invention can confirm whether the operator is the user himself by the sliding distance of the user on the mobile banking page, thereby improving the security of client business operations; in addition, the pages that need to monitor user behavior are screened out, and there is no need to monitor every page, which can reduce the pressure on the back-end server.

[0037] Figure 2 It is a specific example diagram of the user identity authentication method according to an embodiment of the present invention.

[0038] In one embodiment of the present invention, reference Figure 2 , for step 101, the historical operation location data of the user on each page of the mobile banking is collected, and the detailed steps for obtaining the sliding distance data set according to the historical operation location data are as follows:

[0039] Step 201, collecting the user's historical operation initial position coordinates and historical operation end position coordinates on each mobile banking page;

[0040] Step 202, determining the Euclidean distance between the historical operation initial position coordinates and the historical operation end position coordinates as historical sliding distance data;

[0041] Step 203: Obtain a sliding distance data set according to the historical sliding distance data of the user on each page.

[0042] In the specific implementation, JavaScript program is used to obtain the sliding distance data set of users on each mobile banking page according to the following process:

[0043] (1) Listening for touch events: Listening for touch events in an application is done by using the touch event handler provided by the development platform or framework. When a user slides their finger on the screen, a touch event is triggered.

[0044] (2) Recording the initial touch position: When a touch event is triggered, record the initial operation position coordinates, i.e., the initial touch position coordinates (startX, startY), as reference coordinates for calculating the starting point of the sliding distance;

[0045] (3) Listening for sliding events: After the touch event is triggered, as the user's finger slides, a sliding event will be triggered. In the sliding event, the coordinates of the end position of the user's operation (endX, endY) are obtained;

[0046] (4) Calculating the sliding distance: The sliding distance can be obtained by calculating the distance between the initial operation position coordinates and the final operation position coordinates using the Euclidean distance formula;

[0047] (5) By regularly collecting the historical sliding distance data of users on each page, a sliding distance dataset can be obtained.

[0048] In one embodiment of the present invention, clustering calculation is performed on the historical sliding distance data of users on each page in the sliding distance data set according to the characteristic information of each page; specifically, clustering clusters of the historical sliding distance data are set according to the user operation mode on each page; wherein the user operation mode includes: click operation and / or pull-down operation; according to the clustering clusters of the historical sliding distance data, clustering calculation is performed on the historical sliding distance data of users on each page in the sliding distance data set. Before clustering calculation is performed, clustering clusters of the historical sliding distance data are set to improve the accuracy of clustering calculation.

[0049] In one embodiment of the present invention, for step 102, based on the characteristic information of each page, the historical sliding distance data of the user on each page in the sliding distance data set is clustered and calculated, and after the sliding distance data range that meets the user characteristics of each page is determined, it also includes: determining the historical sliding distance data of each page that does not fall into the sliding distance data range that meets the user characteristics as historical sliding distance noise. For example: the sliding distance data range that meets the user characteristics corresponding to the user's click operation on each page (i.e., cluster cluster) is 0.6cm-0.9cm, and the sliding distance data range that meets the user characteristics corresponding to the user's pull-down operation on each page (i.e., cluster cluster) is 1.8cm-2.2cm, then the historical sliding distance data that does not fall into the sliding distance data range that meets the user characteristics corresponding to the click operation and the pull-down operation can be determined as historical sliding distance noise, such as 1.2cm, 2.7cm, etc.

[0050] Figure 3 It is a specific example diagram of the user identity authentication method according to an embodiment of the present invention.

[0051] In one embodiment of the present invention, reference Figure 3 , the detailed steps to confirm the risk event and notify the user are as follows:

[0052] Step 301, clustering the sliding distance data of the user on the page whose user behavior needs to be monitored and the historical sliding distance noise points;

[0053] Step 302: If the sliding distance data of the user on the page whose user behavior needs to be monitored belongs to the same cluster as any historical sliding distance noise point, it is confirmed that the risk event is not operated by the user himself, and the user is notified of the non-user operation message;

[0054] Step 303: If the sliding distance data of the user on the page whose user behavior needs to be monitored does not belong to the same cluster as any historical sliding distance noise point, it is confirmed that the risk event is a user error operation, and a user error operation message is notified to the user.

[0055] In one embodiment of the present invention, the sliding distance data of the user on the page where the user behavior needs to be monitored is clustered with the historical sliding distance noise points. If the sliding distance data of the user on the page falls within the sliding distance data range that meets the user characteristics of the page, it is confirmed that the user himself operates on the page; if the sliding distance data of the user on the page where the user behavior needs to be monitored and any historical sliding distance noise points belong to the same cluster, it is confirmed that the risk event is not an operation by the user himself; if the sliding distance data of the user on the page where the user behavior needs to be monitored and any historical sliding distance noise points do not belong to the same cluster, it is confirmed that the risk event is an incorrect operation by the user. For example: the user's sliding distance data on the page whose user behavior needs to be monitored are 2.1cm, 1.9cm, 3cm and 3.5cm respectively, and the sliding distance data that meets the user's characteristics on the page ranges from 1.8cm to 2.2cm, the historical sliding distance noise points are 1.2cm and 2.7cm, and the preset error range is 0.4cm. It can be confirmed that the operations corresponding to the sliding distance data of 2.1cm and 1.9cm are performed by the user himself on the page; the operation corresponding to the sliding distance data of 3cm is confirmed to be performed by someone other than the user on the page, and the user is notified of the non-user operation message; the operation corresponding to the sliding distance data of 3.5cm is confirmed to be an erroneous operation by the user on the page, and the user is notified of the erroneous operation message.

[0056] In specific implementation, the user uses the mobile banking client to transfer money. During the transaction, the user will trigger the action of sliding the mobile phone screen due to function operations such as switching menus and turning pages. During the sliding screen operation, the system will automatically obtain the sliding distance data on the page where the user behavior needs to be monitored, and cluster the sliding distance data on the page where the user behavior needs to be monitored with the historical sliding distance noise points. If the sliding distance data of the user on the page falls within the sliding distance data range that meets the user's characteristics on the page, it is confirmed that the user himself operates on the page, and the operation determined to be the user himself is set to a pass state; if the user is on the page where the user behavior needs to be monitored, the system will automatically obtain the sliding distance data on the page where the user behavior needs to be monitored, and cluster the sliding distance data on the page where the user behavior needs to be monitored. If the sliding distance data on the page whose user behavior needs to be monitored belongs to the same cluster as any historical sliding distance noise point, it is confirmed that the operation is not performed by the user himself and is marked as a high-risk event. A warning message indicating that the operation is not performed by the user himself is sent to the mobile phone number reserved by the user in the financial system, and a secondary verification is performed using static identity authentication methods such as password login, face recognition, iris recognition, and pulse verification. If the sliding distance data of the user on the page whose user behavior needs to be monitored does not belong to the same cluster as any historical sliding distance noise point, it is confirmed that it is a user error operation and is marked as a general risk event. A warning message indicating that the user has performed a wrong operation is sent to the mobile phone number reserved by the user in the financial system.

[0057] In one embodiment of the present invention, the sliding distance data of the user on the page where the user behavior needs to be monitored is clustered with the historical sliding distance noise points; specifically, according to a preset error range, the DBSCAN algorithm is used to cluster the sliding distance data of the user on the page where the user behavior needs to be monitored with the historical sliding distance noise points.

[0058] In specific implementation, due to the large differences in operations on different financial transaction pages, the sliding distances corresponding to the screen sliding actions triggered by users during the operation will have large differences, and the data is relatively discrete. Therefore, clustering that can discover arbitrary shapes is used and can effectively identify abnormal data noise. The DBSCAN algorithm based on density calculation is used to perform clustering calculations on the historical sliding distance data of users on each page in the sliding distance data set, determine the sliding distance data range that meets the user characteristics of each page, and the historical sliding distance data noise that does not fall into the sliding distance data range that meets the user characteristics, and then use the DBSCAN algorithm to cluster the user's sliding distance data on the page where user behavior needs to be monitored with the historical sliding distance noise.

[0059] In one embodiment of the present invention, the number of historical operations of the user on each page is determined, and pages whose number of historical operations is greater than the average number of historical operations of each page are screened out as pages that need to monitor user behavior.

[0060] In the specific implementation, the number of historical operations of users in each page (i.e., the number of historical slides) is counted, and the average number of historical operations on each page in the entire transaction process is calculated; all pages are traversed to determine whether the number of historical operations on the page is greater than the average. If the number of historical operations on a single page is greater than the average, the page is marked as a page where user behavior needs to be monitored, and the pages where user behavior needs to be monitored are tracked, monitored and analyzed.

[0061] In one embodiment of the present invention, before determining the number of historical operations of the user on each page, the method further includes: setting a data dictionary for each page to record the number of historical operations of the user on each page.

[0062] During the specific implementation, a data dictionary is initialized to record the number of operations (i.e., the number of swipes) performed by the user's finger on each page; the data dictionary is traversed to determine whether the current page has been recorded, and the average number of operations on all pages in the entire transaction process is calculated: swipe_counts_mean = sum(page_swipe_counts.values()) / len(page_swipe_counts); wherein, swipe_counts_mean represents the average number of operations, page_swipe_counts represents the number of operations on each page, and len(page_swipe_counts) represents the number of pages.

[0063] Figure 4 It is a specific example diagram of the user identity authentication method according to an embodiment of the present invention.

[0064] The present invention can collect information from mobile APP, bank self-service financial equipment, bank counter operation and other devices with screen interactive operation, and refer to Figure 4 , collect the historical sliding distance of the user's finger on the screen, perform cluster calculation on the historical sliding distance data of the user on each page of the screen, define the sliding distance data range that meets the user characteristics of each page, and determine the historical sliding distance data of each page that does not fall into the sliding distance data range that meets the user characteristics as the historical sliding distance noise point; monitor the number of operations of the user on each page in real time, filter out the pages with the number of operations greater than the average number of operations of each page as the pages that need to monitor user behavior, obtain the sliding distance data of the user on the page, compare the sliding distance data of the user on the page with the sliding distance data range that meets the user characteristics of the page, analyze and determine the abnormal sliding distance data, and perform non-user Warning for personal operation: If the sliding distance data of the user on the page falls within the sliding distance data range that meets the user's characteristics, it is confirmed that the user himself operates on the page, and the operation determined to be the user himself is set to a pass state; if the sliding distance data of the user on the page where user behavior needs to be monitored belongs to the same cluster as any historical sliding distance noise point, it is confirmed that the risk event is not the user's operation, and the user is notified of the warning message of the non-user operation; if the sliding distance data of the user on the page where user behavior needs to be monitored does not belong to the same cluster as any historical sliding distance noise point, it is confirmed that the risk event is a user error operation, and the user is notified of the user error operation message, thereby completing user identity verification.

[0065] It should be noted that, although the operations of the method of the present invention are described in a specific order in the above embodiments and the accompanying drawings, this does not require or imply that the operations must be performed in the specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0066] The implementation of the user identity authentication device can refer to the implementation of the above method, and the repetitions will not be repeated. The term "module" or "unit" used below can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0067] Based on the same inventive concept, the present invention also proposes a user identity authentication device, such as Figure 5As shown, the device comprises:

[0068] The data collection module 501 is used to collect the historical operation position data of the user on each page of the mobile banking, and obtain the sliding distance data set according to the historical operation position data, and the sliding distance data set records the historical sliding distance data of the user on each page;

[0069] The clustering calculation module 502 is used to perform clustering calculation on the historical sliding distance data of the user on each page in the sliding distance data set according to the characteristic information of each page, and determine the sliding distance data range of each page that meets the user characteristics;

[0070] The page screening module 503 is used to determine the number of historical operations of the user on each page, and screen out pages whose number of historical operations is greater than the average number of historical operations of each page as pages that need to monitor user behavior;

[0071] The data comparison module 504 is used to obtain the sliding distance data of the user on the page when a user operation occurs on the page where the user behavior needs to be monitored, and compare the sliding distance data of the user on the page with the sliding distance data range of the page that meets the user characteristics according to the characteristic information of the page;

[0072] The operation judgment module 505 is used to confirm that the user himself operates on the page if the sliding distance data of the user on the page falls into the sliding distance data range that meets the user characteristics of the page; otherwise, it is confirmed as a risk event and notifies the user himself.

[0073] In one embodiment of the present invention, the data acquisition module 501 is specifically used for:

[0074] Collect the user's historical operation initial location coordinates and historical operation end location coordinates on each page of mobile banking;

[0075] The Euclidean distance between the historical operation initial position coordinates and the historical operation end position coordinates is determined as the historical sliding distance data;

[0076] The sliding distance dataset is obtained based on the historical sliding distance data of users on each page.

[0077] In one embodiment of the present invention, it further includes:

[0078] The noise point determination module is used to perform cluster calculation on the historical sliding distance data of users on each page in the sliding distance data set according to the characteristic information of each page, and after determining the sliding distance data range of each page that meets the user characteristics, the historical sliding distance data of each page that does not fall into the sliding distance data range that meets the user characteristics is determined as a historical sliding distance noise point.

[0079] In one embodiment of the present invention, the clustering calculation module 502 is specifically used for:

[0080] According to the user operation mode on each page, a cluster of historical sliding distance data is set; wherein the user operation mode includes: click operation and / or pull-down operation;

[0081] According to the clustering clusters of the historical sliding distance data, clustering calculation is performed on the historical sliding distance data of users on each page in the sliding distance data set.

[0082] In one embodiment of the present invention, the operation determination module 505 is specifically used for:

[0083] Cluster the user's sliding distance data on the page where user behavior needs to be monitored and the historical sliding distance noise points;

[0084] If the sliding distance data of the user on the page whose user behavior needs to be monitored belongs to the same cluster as any historical sliding distance noise point, it is confirmed that the risk event is not operated by the user himself, and the user is notified of the non-user operation message;

[0085] If the sliding distance data of the user on the page whose user behavior needs to be monitored does not belong to the same cluster as any historical sliding distance noise point, it is confirmed that the risk event is a user error operation, and the user is notified of the user error operation message.

[0086] In one embodiment of the present invention, the operation determination module 505 is specifically used for:

[0087] According to the preset error range, the DBSCAN algorithm is used to cluster the user's sliding distance data on the page where user behavior needs to be monitored and the historical sliding distance noise points.

[0088] In one embodiment of the present invention, it further includes: a times determination module, which is used to set a data dictionary for each page to record the times of historical operations of the user on each page before determining the times of historical operations of the user on each page.

[0089] It should be noted that although several modules of the user identity authentication device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules described above can be concretized in one module. Conversely, the features and functions of one module described above can be further divided into multiple modules to be concretized.

[0090] Based on the above invention concept, Figure 6As shown, the present invention also proposes a computer device 600, including a memory 601, a processor 602, and a computer program 603 stored in the memory 601 and executable on the processor 602, wherein the processor 602 implements the aforementioned user identity authentication method when executing the computer program 603.

[0091] Based on the aforementioned inventive concept, the present invention proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the aforementioned user identity authentication method is implemented.

[0092] The user identity authentication method and device proposed in the embodiment of the present invention can solve the problem in the prior art that static media such as passwords, fingerprints, and faces are easily recorded by criminals, thereby affecting the security of business operations; the embodiment of the present invention collects historical operation position data of users on various pages of mobile banking, obtains a sliding distance data set according to the historical operation position data, and records the historical sliding distance data of users on various pages in the sliding distance data set; according to the characteristic information of each page, cluster calculation is performed on the historical sliding distance data of users on various pages in the sliding distance data set to determine the sliding distance data range of each page that meets the user characteristics; the number of historical operations of users on each page is determined, and pages with historical operation times greater than the average number of historical operation times of each page are screened out as pages that need to monitor user behavior; when a user operation occurs on a page that needs to monitor user behavior, the sliding distance data of the user on the page is obtained, and according to the characteristic information of the page, the sliding distance data of the user on the page is compared with the sliding distance data range of the page that meets the user characteristics; if the sliding distance data of the user on the page falls into the sliding distance data range that meets the user characteristics of the page, it is confirmed that the user himself operates on the page; otherwise, it is confirmed as a risk event and the user himself is notified. The embodiment of the present invention can confirm whether the operator is the user himself by the sliding distance of the user on the mobile banking page, and provide a security warning notification to improve the security of client business operations; in addition, the pages that need to monitor user behavior are screened out, and there is no need to monitor every page, which can reduce the pressure on the back-end server.

[0093] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0094] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0095] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0096] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0097] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A user identity authentication method, characterized in that: include: Collect the historical operation location data of users on each page of mobile banking, and obtain the sliding distance data set based on the historical operation location data. The sliding distance data set records the historical sliding distance data of users on each page; According to the characteristic information of each page, cluster calculation is performed on the historical sliding distance data of users on each page in the sliding distance data set to determine the sliding distance data range of each page that meets the user characteristics; Determine the historical operation times of the user on each page, and select the pages whose historical operation times are greater than the average of the historical operation times of each page as the pages that need to monitor user behavior; When a user operation occurs on a page whose user behavior needs to be monitored, the sliding distance data of the user on the page is obtained, and according to the characteristic information of the page, the sliding distance data of the user on the page is compared with the sliding distance data range of the page that meets the user characteristics; If the user's sliding distance data on the page falls within the sliding distance data range that matches the user's characteristics, it is confirmed that the user himself operated on the page; otherwise, it is confirmed as a risk event and the user is notified.

2. The method according to claim 1, characterized in that Collect the historical operation location data of users on each page of mobile banking, and obtain the sliding distance data set based on the historical operation location data, including: Collect the user's historical operation initial location coordinates and historical operation end location coordinates on each page of mobile banking; The Euclidean distance between the historical operation initial position coordinates and the historical operation end position coordinates is determined as the historical sliding distance data; The sliding distance dataset is obtained based on the historical sliding distance data of users on each page.

3. The method according to claim 1, characterized in that According to the characteristic information of each page, cluster calculation is performed on the historical sliding distance data of users on each page in the sliding distance dataset, including: According to the user operation mode on each page, a cluster of historical sliding distance data is set; wherein the user operation mode includes: click operation and / or pull-down operation; According to the clustering clusters of the historical sliding distance data, clustering calculation is performed on the historical sliding distance data of users on each page in the sliding distance data set.

4. The method according to claim 1, characterized in that: According to the characteristic information of each page, clustering calculation is performed on the historical sliding distance data of the user on each page in the sliding distance data set, and after determining the sliding distance data range of each page that meets the user characteristics, it also includes: The historical sliding distance data of each page that does not fall into the sliding distance data range that meets the user characteristics is determined as the historical sliding distance noise point.

5. The method according to claim 4, characterized in that Confirm the risk event and notify the user, including: Cluster the user's sliding distance data on the page where user behavior needs to be monitored and the historical sliding distance noise points; If the sliding distance data of the user on the page whose user behavior needs to be monitored belongs to the same cluster as any historical sliding distance noise point, it is confirmed that the risk event is not operated by the user himself, and the user is notified of the non-user operation message; If the sliding distance data of the user on the page whose user behavior needs to be monitored does not belong to the same cluster as any historical sliding distance noise point, it is confirmed that the risk event is a user error operation, and the user is notified of the user error operation message.

6. The method according to claim 5, characterized in that Cluster the user's sliding distance data on the page where user behavior needs to be monitored and the historical sliding distance noise points, including: According to the preset error range, the DBSCAN algorithm is used to cluster the user's sliding distance data on the page where user behavior needs to be monitored and the historical sliding distance noise points.

7. The method according to claim 1, characterized in that Before determining the number of historical operations of users on each page, it also includes: Set a data dictionary for each page to record the number of historical operations performed by users on each page.

8. A user identity authentication device, characterized in that: include: The data collection module is used to collect the historical operation location data of the user on each page of the mobile banking, and obtain the sliding distance data set according to the historical operation location data. The sliding distance data set records the historical sliding distance data of the user on each page; The clustering calculation module is used to perform clustering calculation on the historical sliding distance data of the user on each page in the sliding distance data set according to the characteristic information of each page, and determine the sliding distance data range of each page that meets the user characteristics; The page screening module is used to determine the number of historical operations of the user on each page, and screen out pages whose number of historical operations is greater than the average number of historical operations of each page as pages that need to monitor user behavior; A data comparison module is used to obtain the sliding distance data of the user on the page when a user operation occurs on the page where the user behavior needs to be monitored, and compare the sliding distance data of the user on the page with the sliding distance data range of the page that meets the user characteristics according to the characteristic information of the page; The operation judgment module is used to confirm that the user has operated on the page if the sliding distance data of the user on the page falls within the sliding distance data range that meets the user's characteristics; otherwise, it is confirmed as a risk event and notifies the user himself.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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