Security tool identification methods, devices, computer equipment and storage media

Abstract

This application relates to a method, apparatus, computer device, storage medium, and computer program product for identifying security tools. The method includes: inputting an image of a bank security tool into a preset recognition model to obtain category information of the bank security tool; the recognition model is trained using a sample set of bank security tools; the sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images; and sending the category information of the bank security tool to the user. This method can improve the accuracy of identifying bank security tools.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence recognition and classification technology, and in particular to a method, apparatus, computer equipment, storage medium and computer program product for identifying security tools. Background Technology

[0002] With the widespread use of online banking, users can conduct online banking operations using security tools such as online banking tokens. Online banking tokens are a commonly used security tool for bank customers; different banks offer different tokens, and even different generations of tokens from the same bank can differ. When a user has multiple online banking tokens, it is necessary to distinguish between them when using them.

[0003] Currently, when classifying and identifying different online banking security tokens, users can do so based on the information labels affixed to the tokens. However, users cannot distinguish between tokens with missing or damaged information labels. Summary of the Invention

[0004] Therefore, it is necessary to provide a security tool identification method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can improve the accuracy of identifying bank security tools, addressing the aforementioned technical problems.

[0005] Firstly, this application provides a method for identifying security tools. The method includes:

[0006] The image of a bank security tool is input into a preset recognition model to obtain the category information of the bank security tool; the recognition model is trained using a sample set of bank security tools; the sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images; the category information of the bank security tool includes the bank identifier of the bank to which the bank security tool belongs; the category information of the bank security tool is sent to the user.

[0007] In one embodiment, the category information for bank security tools also includes the product version corresponding to the bank security tool.

[0008] In one embodiment, the method further includes:

[0009] Obtain the login status of the bank security tools output by the preset test system; the login status is used to indicate whether the bank security tools can log in to the bank system normally; match the category information of the bank security tools with the login status, and upgrade the system according to the matching results.

[0010] In one embodiment, the category information of bank security tools is matched with the login status, and the system is upgraded based on the matching result, including:

[0011] If the login status indicates that the bank security tool has successfully logged into the first bank's banking system, and the category information indicates that the bank security tool belongs to the second bank, then the first upgrade instruction for the first bank's banking system will be output; if the login status indicates that the bank security tool has failed to log into the first bank's banking system, and the category information indicates that the bank security tool belongs to the first bank, then the second upgrade instruction for the bank security tool will be output.

[0012] In one embodiment, the method further includes:

[0013] Obtain test instructions triggered by the user on the test system; in response to the test instructions, invoke the camera connected to the test system to capture images of the bank's security tools.

[0014] In one embodiment, the method further includes:

[0015] Obtain a sample set of bank security tools; use the sample images in the sample set as the reference input of the initial recognition model, and use the category labels of the bank security tools corresponding to the sample images as the reference output of the initial recognition model. Train the initial recognition model according to the preset loss function to obtain the preset recognition model.

[0016] Secondly, this application also provides a security tool identification device. The device includes:

[0017] The input module is used to input images of bank security tools into a preset recognition model to obtain category information of the bank security tools. The recognition model is trained using a sample set of bank security tools. The sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images. The category information of the bank security tools includes the bank identifier of the bank to which the bank security tool belongs.

[0018] The sending module is used to send category information of bank security tools to users.

[0019] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method steps of any of the embodiments of the first aspect described above.

[0020] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the method steps of any of the embodiments of the first aspect described above.

[0021] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the method steps described in any of the embodiments of the first aspect.

[0022] The aforementioned security tool identification method, apparatus, computer equipment, storage medium, and computer program product obtain the category information of bank security tools by inputting images of bank security tools into a preset identification model; and then send the category information of bank security tools to the user. In the technical solution provided in this application embodiment, for security tools with missing or unattached information tags, the category information of the security tool can be obtained by capturing images of the security tool and inputting them into the identification model for calculation. This allows users to accurately distinguish security tools from different banks based on the category information calculated by the identification model. Furthermore, even when a user possesses a large number of different types of security tools, the category information of the security tools can be obtained quickly. Moreover, since the identification model is pre-trained using sample images of multiple bank security tools and the category tags of the bank security tools in the sample images, the accuracy of identifying bank security tools is improved by using this trained identification model to identify the images of the security tools. Attached Figure Description

[0023] Figure 1 This is an internal structural diagram of a computer device in one embodiment;

[0024] Figure 2 This is a flowchart illustrating a security tool identification method in one embodiment;

[0025] Figure 3 This is a flowchart illustrating the processing of category information for bank security tools in one embodiment;

[0026] Figure 4 This is a flowchart illustrating the process of acquiring images of bank security tools in one embodiment;

[0027] Figure 5 This is a schematic diagram of the process for generating a preset recognition model in one embodiment;

[0028] Figure 6 This is an architecture diagram of reinforcement learning in one embodiment;

[0029] Figure 7 This is a flowchart illustrating the design process of the AlexNet convolutional neural network classification model in one embodiment.

[0030] Figure 8 Here is a network structure diagram of the AlexNet convolutional neural network classification model in one embodiment;

[0031] Figure 9 This is an overall architecture diagram for security tool identification in one embodiment;

[0032] Figure 10 This is a structural block diagram of a security tool identification device in one embodiment. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0034] The security tool identification method provided in this application can be applied to computer devices, which can be servers or terminals. The server can be a single server or a server cluster composed of multiple servers. This application does not specifically limit this. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices.

[0035] Taking a computer device as an example, Figure 1 A block diagram of a server is shown, such as Figure 1 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores security tool identification data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a security tool identification method.

[0036] Those skilled in the art will understand that Figure 1 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the server to which the present application is applied. Optionally, the server may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0037] It should be noted that the execution subject of the embodiments of this application can be a computer device or a security tool identification device. The following method embodiments will be described with a computer device as the execution subject.

[0038] In one embodiment, such as Figure 2The diagram illustrates a flowchart of a security tool identification method provided in an embodiment of this application. This method may include the following steps:

[0039] Step 220: Input the image of the bank security tool into the preset recognition model to obtain the category information of the bank security tool; the recognition model is trained using a sample set of bank security tools; the sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images; the category information of the bank security tool includes the bank identifier of the bank to which the bank security tool belongs.

[0040] Step 240: Send the user the category information of the bank's security tools.

[0041] Among them, bank security tools are tools used to support users in conveniently and securely operating online banking. These tools can be online banking tokens and their upgraded versions, USB flash drives, external network cards, Bluetooth receivers, etc., and other types of bank security tools are also possible; this embodiment does not specifically limit them. Images from the bank security tools can be captured in real-time by an image acquisition device and then input into a preset recognition model. Alternatively, images captured by the image acquisition device can be pre-stored locally or in a database, and then input into the preset recognition model by reading the pre-stored images.

[0042] The image of the bank security tool can be directly input into a preset recognition model, or it can be preprocessed before being input into the preset recognition model. Preprocessing operations can include at least one of image resizing, image normalization, and image enhancement, and may also include other image processing procedures. This embodiment does not specifically limit the type of preprocessing operation. Optionally, image resizing can be achieved using bicubic interpolation, for example, transforming the image size to 227*227. Image normalization can be achieved by linearly transforming the image pixel values ​​and mapping the data to the range [0,1]. Image enhancement can be achieved by scaling the image to a ratio of equal width and height to control the data size. Furthermore, a random cropping method can be used to randomly extract a 227*227 image block from five locations in the image of the bank security tool, namely the four corners and the center. This embodiment also does not specifically limit the specific implementation method of the preprocessing operation.

[0043] The preset recognition model is used to identify the category information of bank security tools. The recognition model can be a neural network model; this embodiment does not specifically limit the type of neural network model, for example, it can be an AlexNet convolutional neural network model. The recognition model is trained using a sample set of bank security tools. The sample set can include sample images of multiple bank security tools and category labels for the bank security tools in the sample images. The category labels for the bank security tools in the sample images can be manually labeled based on prior knowledge. The recognition model can extract features from the input images of bank security tools, obtaining features such as shape, size, color, and functional distribution. Based on the extracted features, the category information of the bank security tool is calculated and output, and this category information can be sent to the user. The category information of bank security tools can be used to distinguish bank security tools from different banks. Therefore, the category information of bank security tools includes the bank's identifier. For bank security tools from different banks, their shape, size, color, functional distribution, and other features will have certain differences. By recognizing the images of bank security tools, the bank's identifier can be obtained.

[0044] In this embodiment, the category information of bank security tools is obtained by inputting images of the tools into a preset recognition model; this category information is then sent to the user. For security tools with missing or unattached information tags, the category information can be obtained by capturing images of the tools and inputting them into the recognition model for calculation. This allows users to accurately distinguish between security tools from different banks based on the category information calculated by the recognition model. Furthermore, even when a user possesses a large number of different types of security tools, the category information can be quickly obtained. Moreover, since the recognition model is pre-trained using sample images of multiple bank security tools and their category tags, the accuracy of identifying bank security tools is improved.

[0045] In one embodiment, the category information of bank security tools also includes the product version corresponding to the bank security tool. This category information can be used to distinguish bank security tools from different banks, and also to differentiate between different versions of bank security tools from the same bank. Therefore, the category information of bank security tools includes the bank's identifier and may also include the corresponding product version. Bank security tools from different banks will have certain differences in shape, size, color, and functional distribution, and even different versions of bank security tools from the same bank will have differences in these characteristics. By refining the classification information, different types of bank security tools can be more accurately distinguished.

[0046] In one embodiment, such as Figure 3 The diagram illustrates a flowchart of a security tool identification method provided in an embodiment of this application. Specifically, it relates to a possible process for processing category information of bank security tools, which may include the following steps:

[0047] Step 320: Obtain the login status of the bank security tool output by the preset test system; the login status is used to indicate whether the bank security tool can log in to the bank system normally.

[0048] Step 340: Match the category information of bank security tools with the login status, and upgrade the system based on the matching results.

[0049] Before a bank security tool is put into use, internal bank personnel can test it. For example, they can test the login function of the security tool on the bank system. Specifically, they can obtain the login status of the security tool output by the preset test system, match the category information of the security tool with the login status, and upgrade the system based on the matching results.

[0050] Optionally, if the login status indicates that the bank security tool has successfully logged into the first bank's banking system, and the category information indicates that the bank security tool belongs to the second bank, then a first upgrade instruction for the first bank's banking system is output. Here, the first bank and the second bank have different bank identifiers. So, when the bank security tool belonging to the second bank can successfully log into the first bank's banking system, the first upgrade instruction needs to be output, and the first bank's banking system is upgraded according to the first upgrade instruction. If the login status indicates that the bank security tool has failed to log into the first bank's banking system, and the category information indicates that the bank security tool belongs to the first bank, then a second upgrade instruction for the bank security tool is output. So, when the bank security tool belonging to the first bank cannot successfully log into the first bank's banking system, the second upgrade instruction needs to be output, and the first bank's bank security tool is upgraded according to the second upgrade instruction.

[0051] In this embodiment, the login status of the bank security tool output by the preset test system is obtained, and the category information of the bank security tool is matched with the login status. Based on the matching result, the system is upgraded. By matching the category information of the bank security tool with the login status, the login function of the bank security tool to be tested on the bank system is tested, and corresponding upgrade operations are performed based on the test results. This not only improves the security of using the bank security tool, but also improves the security of the bank system.

[0052] In one embodiment, such as Figure 4 The diagram illustrates a flowchart of a security tool identification method provided in an embodiment of this application. Specifically, it relates to a possible process for acquiring images of bank security tools, and the method may include the following steps:

[0053] Step 420: Obtain the test instructions triggered by the user on the test system.

[0054] Step 440: In response to the test instruction, call the camera connected to the test system to capture images of the bank's security tools.

[0055] When users test bank security tools, they need to first obtain the category information of the bank security tools. This requires capturing images of the bank security tools. Specifically, this can be done by receiving test instructions triggered by the user on the test system, responding to the test instructions, and calling the camera connected to the test system to capture images of the bank security tools. By automatically calling the camera to capture images of the bank security tools, the subsequent recognition process is carried out, and the recognition results can be displayed to the user.

[0056] In this embodiment, by obtaining the test instruction triggered by the user on the test system and responding to the test instruction, the camera connected to the test system is invoked to collect images of the bank security tools. The method of automatically invoking the camera to collect images in response to the test instruction is more convenient, thereby improving the efficiency of users testing bank security tools.

[0057] In one embodiment, such as Figure 5 The diagram illustrates a flowchart of a security tool identification method provided in an embodiment of this application. Specifically, it relates to a possible process for generating a preset identification model, which may include the following steps:

[0058] Step 520: Obtain a sample set of bank security tools.

[0059] Step 540: Use the sample images in the sample set as the reference input of the initial recognition model, and use the category label of the bank security tool corresponding to the sample image as the reference output of the initial recognition model. Train the initial recognition model according to the preset loss function to obtain the preset recognition model.

[0060] In training the recognition model, it is necessary to first obtain a sample set of bank security tools. The sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images. The sample set can be obtained from a pre-built bank security tool image database. The sample images in the sample set are used as the reference input of the initial recognition model, and the category labels of the bank security tools corresponding to the sample images are used as the reference output of the initial recognition model. Then, the model parameters of the initial recognition model are adjusted according to the reference output, category labels, and a preset loss function, thereby generating a preset recognition model based on the adjusted model parameters.

[0061] In actual use, such as Figure 6 As shown, Figure 6 This application provides an architecture diagram for reinforcement learning, which can further update the bank security tool image database based on the output of the recognition model and the user's feedback. For example, if the output of the recognition model is inconsistent with the user's feedback, and the feedback includes the correct category information of the bank security tool, then the category labels corresponding to the bank security tools in the bank security tool image database are updated according to the user's feedback. The updated bank security tool image database can also be used to retrain the recognition model, thereby realizing the reinforcement learning process of the bank security tool recognition system and improving the accuracy of the recognition model.

[0062] In one embodiment, the aforementioned preset recognition model can choose the TensorFlow deep learning open-source framework as its model design framework, and the recognition model can adopt the AlexNet convolutional neural network classification model. The design process of the AlexNet convolutional neural network classification model is as follows: Figure 7 As shown, its network structure is as follows Figure 8 As shown. For this AlexNet convolutional neural network classification model, its activation function can be the LRN local response normalization function used after activation and pooling; its parameter settings can be adjusted from aspects such as batch size, initial learning rate, and dropout random inactivation probability. In addition, the network structure can be optimized by changing the number of convolutional kernels in the network layers, the number of parameters in the fully connected layers, and the standard deviation parameter value of the truncated normal distribution.

[0063] In one specific embodiment, such as Figure 9 As shown, Figure 9 This application provides an overall architecture diagram for identifying security tools. When identifying bank security tools, the user can first acquire an image of the bank security tool to be identified through a terminal image input device, i.e., a camera or a handheld mobile device with recording function. The acquired image is then uploaded to the server. The server's preset recognition model identifies the input image to obtain the classification information of the bank security tool. The classification information can be output on the display screen, and the user can distinguish the category of the bank security tool based on the classification information on the display screen.

[0064] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0065] Based on the same inventive concept, this application also provides a security tool identification device for implementing the security tool identification method described above. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more security tool identification device embodiments provided below can be found in the limitations of the security tool identification method described above, and will not be repeated here.

[0066] In one embodiment, such as Figure 10 As shown, a security tool identification device 1000 is provided, including: an input module 1002 and a sending module 1004, wherein:

[0067] The input module 1002 is used to input images of bank security tools into a preset recognition model to obtain category information of the bank security tools; the recognition model is trained using a sample set of bank security tools; the sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images; the category information of the bank security tools includes the bank identifier of the bank to which the bank security tool belongs.

[0068] The sending module 1004 is used to send category information of bank security tools to users.

[0069] In one embodiment, the category information of a bank security tool includes the bank identifier of the bank to which the bank security tool belongs.

[0070] In one embodiment, the category information for bank security tools may also include the product version corresponding to the bank security tool.

[0071] In one embodiment, the security tool identification device 1000 further includes a first acquisition module and a matching module, wherein:

[0072] The first acquisition module is used to acquire the login status of the bank security tool output by the preset test system; the login status is used to indicate whether the bank security tool can log in to the bank system normally; the matching module is used to match the category information of the bank security tool with the login status, and upgrade the system according to the matching result.

[0073] In one embodiment, the matching module is further configured to output a first upgrade instruction for the first bank's banking system if the login status indicates that the bank security tool has logged into the first bank's banking system normally, and the category information indicates that the bank security tool belongs to the second bank; and output a second upgrade instruction for the bank security tool if the login status indicates that the bank security tool has logged into the first bank's banking system abnormally, and the category information indicates that the bank security tool belongs to the first bank.

[0074] In one embodiment, the security tool identification device 1000 further includes a second acquisition module and a recall module, wherein:

[0075] The second acquisition module is used to acquire test instructions triggered by the user on the test system; the invocation module is used to respond to the test instructions and invoke the camera connected to the test system to capture images of the bank's security tools.

[0076] In one embodiment, the security tool identification device 1000 further includes a third acquisition module and a training module, wherein:

[0077] The third acquisition module is used to acquire a sample set of bank security tools; the training module is used to take the sample images in the sample set as the reference input of the initial recognition model, take the category label of the bank security tool corresponding to the sample image as the reference output of the initial recognition model, train the initial recognition model according to the preset loss function, and obtain the preset recognition model.

[0078] Each module in the aforementioned security tool identification device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0079] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0080] The image of a bank security tool is input into a preset recognition model to obtain the category information of the bank security tool; the recognition model is trained using a sample set of bank security tools; the sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images; the category information of the bank security tool includes the bank identifier of the bank to which the bank security tool belongs; the category information of the bank security tool is sent to the user.

[0081] In one embodiment, the category information for bank security tools may also include the product version corresponding to the bank security tool.

[0082] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0083] Obtain the login status of the bank security tools output by the preset test system; the login status is used to indicate whether the bank security tools can log in to the bank system normally; match the category information of the bank security tools with the login status, and upgrade the system according to the matching results.

[0084] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0085] If the login status indicates that the bank security tool has successfully logged into the first bank's banking system, and the category information indicates that the bank security tool belongs to the second bank, then the first upgrade instruction for the first bank's banking system will be output; if the login status indicates that the bank security tool has failed to log into the first bank's banking system, and the category information indicates that the bank security tool belongs to the first bank, then the second upgrade instruction for the bank security tool will be output.

[0086] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0087] Obtain test instructions triggered by the user on the test system; in response to the test instructions, invoke the camera connected to the test system to capture images of the bank's security tools.

[0088] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0089] Obtain a sample set of bank security tools; use the sample images in the sample set as the reference input of the initial recognition model, and use the category labels of the bank security tools corresponding to the sample images as the reference output of the initial recognition model. Train the initial recognition model according to the preset loss function to obtain the preset recognition model.

[0090] The computer device provided in this application embodiment has a similar implementation principle and technical effect to the above method embodiment, and will not be described again here.

[0091] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0092] The image of a bank security tool is input into a preset recognition model to obtain the category information of the bank security tool; the recognition model is trained using a sample set of bank security tools; the sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images; the category information of the bank security tool includes the bank identifier of the bank to which the bank security tool belongs; the category information of the bank security tool is sent to the user.

[0093] In one embodiment, the category information for bank security tools may also include the product version corresponding to the bank security tool.

[0094] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0095] Obtain the login status of the bank security tools output by the preset test system; the login status is used to indicate whether the bank security tools can log in to the bank system normally; match the category information of the bank security tools with the login status, and upgrade the system according to the matching results.

[0096] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0097] If the login status indicates that the bank security tool has successfully logged into the first bank's banking system, and the category information indicates that the bank security tool belongs to the second bank, then the first upgrade instruction for the first bank's banking system will be output; if the login status indicates that the bank security tool has failed to log into the first bank's banking system, and the category information indicates that the bank security tool belongs to the first bank, then the second upgrade instruction for the bank security tool will be output.

[0098] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0099] Obtain test instructions triggered by the user on the test system; in response to the test instructions, invoke the camera connected to the test system to capture images of the bank's security tools.

[0100] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0101] Obtain a sample set of bank security tools; use the sample images in the sample set as the reference input of the initial recognition model, and use the category labels of the bank security tools corresponding to the sample images as the reference output of the initial recognition model. Train the initial recognition model according to the preset loss function to obtain the preset recognition model.

[0102] The computer-readable storage medium provided in this embodiment is similar in principle and technical effect to the method embodiment described above, and will not be repeated here.

[0103] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0104] The image of a bank security tool is input into a preset recognition model to obtain the category information of the bank security tool; the recognition model is trained using a sample set of bank security tools; the sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images; the category information of the bank security tool includes the bank identifier of the bank to which the bank security tool belongs; the category information of the bank security tool is sent to the user.

[0105] In one embodiment, the category information for bank security tools may also include the product version corresponding to the bank security tool.

[0106] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0107] Obtain the login status of the bank security tools output by the preset test system; the login status is used to indicate whether the bank security tools can log in to the bank system normally; match the category information of the bank security tools with the login status, and upgrade the system according to the matching results.

[0108] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0109] If the login status indicates that the bank security tool has successfully logged into the first bank's banking system, and the category information indicates that the bank security tool belongs to the second bank, then the first upgrade instruction for the first bank's banking system will be output; if the login status indicates that the bank security tool has failed to log into the first bank's banking system, and the category information indicates that the bank security tool belongs to the first bank, then the second upgrade instruction for the bank security tool will be output.

[0110] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0111] Obtain test instructions triggered by the user on the test system; in response to the test instructions, invoke the camera connected to the test system to capture images of the bank's security tools.

[0112] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0113] Obtain a sample set of bank security tools; use the sample images in the sample set as the reference input of the initial recognition model, and use the category labels of the bank security tools corresponding to the sample images as the reference output of the initial recognition model. Train the initial recognition model according to the preset loss function to obtain the preset recognition model.

[0114] The computer program product provided in this embodiment has a similar implementation principle and technical effect to the method embodiment described above, and will not be repeated here.

[0115] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0116] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. 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). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0117] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0118] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for identifying security tools, characterized in that, The method includes: The system obtains test instructions triggered by the user on the test system, inputs images of bank security tools into a preset recognition model, and obtains the category information of the bank security tools. The recognition model is trained using a sample set of bank security tools. The sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images. The category information of the bank security tools includes the bank identifier of the bank to which the bank security tool belongs and the product version corresponding to the bank security tool. Send the user the category information of the bank's security tools; The category information of the bank security tool is matched with the login status to test the login function of the bank security tool on the bank system; the login status is used to characterize whether the bank security tool can log in to the bank system normally. If the test result indicates that the login status represents that the bank security tool has successfully logged into the banking system of the first bank, and the category information indicates that the bank security tool belongs to the second bank, then the first upgrade instruction for the banking system of the first bank will be output. If the test result indicates that the login status indicates an abnormal login to the first bank's banking system by the bank security tool, and the category information indicates that the bank security tool belongs to the first bank, then the second upgrade instruction for the bank security tool will be output.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the login status of the bank security tool as output by the preset test system.

3. The method according to claim 1 or 2, characterized in that, Before inputting images of bank security tools into a preset recognition model, the method further includes: In response to the test instruction, the camera connected to the test system is invoked to capture images of the bank security tool.

4. The method according to claim 1 or 2, characterized in that, The method further includes: Obtain the sample set of bank security tools; The sample images in the sample set are used as the reference input of the initial recognition model, and the category labels of the bank security tools corresponding to the sample images are used as the reference output of the initial recognition model. The initial recognition model is trained according to a preset loss function to obtain the preset recognition model.

5. A security tool identification device, characterized in that, The device includes: The input module is used to acquire test instructions triggered by the user on the test system, input images of bank security tools into a preset recognition model, and obtain category information of the bank security tools. The recognition model is trained using a sample set of bank security tools. The sample set includes sample images of multiple bank security tools and category labels of the bank security tools in the sample images. The category information of the bank security tools includes the bank identifier of the bank to which the bank security tool belongs and the product version corresponding to the bank security tool. The sending module is used to send the category information of the bank security tools to the user; The matching module is used to match the category information of the bank security tool with the login status to test the login function of the bank security tool on the bank system. The login status is used to indicate whether the bank security tool can log in to the bank system normally. If the test result shows that the login status indicates that the bank security tool can log in to the first bank's bank system normally, and the category information indicates that the bank security tool belongs to the second bank, then a first upgrade instruction for the first bank's bank system is output. If the test result shows that the login status indicates that the bank security tool cannot log in to the first bank's bank system normally, and the category information indicates that the bank security tool belongs to the first bank, then a second upgrade instruction for the bank security tool is output.

6. The apparatus according to claim 5, characterized in that, The device further includes a first acquisition module and a matching module, used to acquire the login status of the bank security tool output by a preset test system.

7. The apparatus according to claim 5 or 6, characterized in that, The device also includes a calling module, used to call a camera connected to the test system to capture images of the bank security tool in response to the test instruction.

8. The apparatus according to claim 5 or 6, characterized in that, The device further includes a third acquisition module and a training module, wherein: The third acquisition module is used to acquire the sample set of bank security tools; The training module is used to take the sample images in the sample set as the reference input of the initial recognition model, take the category label of the bank security tool corresponding to the sample image as the reference output of the initial recognition model, and train the initial recognition model according to the preset loss function to obtain the preset recognition model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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