Application file management method and device, computer equipment and storage medium

Abstract

The embodiment of the invention belongs to the technical field of artificial intelligence, is suitable for the field of finance or medical treatment, and relates to an application file management method and device, computer equipment and a storage medium. The method comprises the steps that when it is monitored that a new application is started, integrity detection operation is conducted on a current application file of the new application, obtaining an integrity detection result; judging whether the integrity detection result is abnormal or not; if the integrity detection result is not abnormal, running the new application program; if the integrity detection result is abnormal, performing file repair operation on the current application file according to a CDN technology to obtain a complete application file corresponding to the new application program; and running the new application program according to the complete application file. Through combination of integrity detection and CDN repair, safe starting and rapid recovery of the application program are realized, and starting failures or security risks caused by file problems are remarkably reduced.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and is applicable to the financial or medical fields, and in particular to an application file management method, apparatus, computer equipment, and storage medium. Background Art

[0002] In the prior art, there is a technology that uses CDN and other technologies to implement program updates and maintenance operations.

[0003] However, the applicant found that if it is a computer program, when the user accidentally deletes the program or the antivirus software accidentally deletes the key program files, causing the program to start abnormally, the existing technical solution will only prompt the user with information such as file damage or missing, thereby causing the user process to be blocked and unable to run normally.

[0004] This shows that traditional program update and maintenance technologies cannot solve the problems of startup failure or security risks caused by file problems. Summary of the Invention

[0005] The purpose of the embodiments of the present application is to propose an application file management method, apparatus, computer equipment and storage medium to solve the problem that traditional program update and maintenance technologies cannot solve the problem of startup failure or security risks caused by file problems.

[0006] In order to solve the above technical problems, the present application provides an application file management method, which adopts the following technical solutions:

[0007] When a new application is detected to be started, an integrity check operation is performed on the current application file of the new application to obtain an integrity check result;

[0008] Determining whether the integrity test result is abnormal;

[0009] If there is no abnormality in the integrity check result, running the new application;

[0010] If the integrity check result is abnormal, performing a file repair operation on the current application file according to CDN technology to obtain a complete application file corresponding to the new application;

[0011] The new application program is run according to the complete application file.

[0012] Furthermore, when a new application is detected to be started, the step of performing an integrity check on the current application file of the new application to obtain an integrity check result specifically includes the following steps:

[0013] The trained anomaly recognition model is called, and the current application file of the new application is input into the trained anomaly recognition model to perform an anomaly recognition operation to obtain the integrity detection result.

[0014] Furthermore, before the step of inputting the current application file of the new application into the trained anomaly recognition model to perform an anomaly recognition operation and obtain the integrity detection result, the following steps are also included:

[0015] Obtaining a historical integrity check result corresponding to the new application;

[0016] An initialization anomaly recognition model is constructed, and a model training operation is performed on the anomaly recognition model according to the historical integrity detection result to obtain the trained anomaly recognition model.

[0017] Furthermore, if the integrity check result is abnormal, performing a file repair operation on the current application file according to CDN technology to obtain a complete application file corresponding to the new application program specifically includes the following steps:

[0018] Determining the abnormal type of the application file according to the integrity detection result;

[0019] Calling a trained repair strategy identification model, and inputting the abnormality type data into the repair strategy identification model to perform a repair strategy identification operation to obtain a CDN repair strategy;

[0020] Perform a file repair operation on the current application file according to the CDN repair strategy to obtain the complete application file.

[0021] Furthermore, before the step of calling the trained repair strategy identification model and inputting the abnormality type data into the repair strategy identification model to perform a repair strategy identification operation to obtain the CDN repair strategy, the following steps are also included:

[0022] Reading a system database, and obtaining abnormal file data, repair operation data, and CDN node information that occurred in historical applications from the system database;

[0023] Performing a key feature extraction operation on the abnormal file data, the repair operation data, and the CDN node information to obtain a target key feature extraction result;

[0024] An initialization repair strategy identification model is constructed, and a model training operation is performed on the initialization repair strategy identification model according to the target key feature extraction result to obtain the trained repair strategy identification model.

[0025] Furthermore, the step of performing a key feature extraction operation on the abnormal file data, the repair operation data, and the CDN node information to obtain a target key feature extraction result specifically includes the following steps:

[0026] Performing a key feature extraction operation on the abnormal file data, the repair operation data, and the CDN node information to obtain an initial key feature extraction result;

[0027] A feature screening operation is performed on the initial key feature extraction result according to a feature selection algorithm to obtain the target key feature extraction result that has the greatest impact on the optimization of the repair strategy.

[0028] In order to solve the above technical problems, the embodiment of the present application further provides an application file management device, which adopts the following technical solution:

[0029] The integrity detection module is used to perform an integrity detection operation on the current application file of the new application when a new application is detected to be started, and obtain an integrity detection result;

[0030] An abnormality judgment module, used to judge whether there is an abnormality in the integrity detection result;

[0031] A first detection result module, configured to run the new application if there is no abnormality in the integrity detection result;

[0032] a second detection result module, configured to, if the integrity detection result is abnormal, perform a file repair operation on the current application file according to CDN technology to obtain a complete application file corresponding to the new application;

[0033] A program running module is used to run the new application program according to the complete application file.

[0034] Furthermore, the calculation module includes:

[0035] The integrity detection submodule is used to call the trained exception recognition model and input the current application file of the new application into the trained exception recognition model to perform an exception recognition operation to obtain the integrity detection result.

[0036] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0037] The system comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the application file management method described above when executing the computer-readable instructions.

[0038] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0039] The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the application file management method described above.

[0040] The present application provides an application file management method, comprising: when a new application is detected to be started, performing an integrity check operation on the current application file of the new application to obtain an integrity check result; determining whether the integrity check result contains any abnormalities; if the integrity check result contains no abnormalities, running the new application; if the integrity check result contains any abnormalities, performing a file repair operation on the current application file according to CDN technology to obtain a complete application file corresponding to the new application; and running the new application according to the complete application file. Compared with the prior art, the present application achieves secure startup and rapid recovery of applications through the combination of integrity detection and CDN repair, significantly reducing startup failures or security risks caused by file problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the solutions in this application, a brief introduction will be given below to the drawings required for use in the description of the embodiments of this application. Obviously, the drawings described below are some embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0042] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0043] Figure 2 This is a flowchart of the implementation of the application file management method provided in the embodiment of the present application;

[0044] Figure 3 This is a schematic diagram of the structure of the application file management device provided in an embodiment of the present application;

[0045] Figure 4 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which this application belongs. The terms used in the specification of the application are for the purpose of describing specific embodiments only and are not intended to limit this application. The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0047] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0048] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0049] like Figure 1 As shown, system architecture 100 may include a terminal device 101, a network 102, and a server 103. Terminal device 101 may be a laptop computer 1011, a tablet computer 1012, or a mobile phone 1013. Network 102 is a medium for providing a communication link between terminal device 101 and server 103. Network 102 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0050] The user can use the terminal device 101 to interact with the server 103 via the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0051] The terminal device 101 can be various electronic devices with a display screen and supporting web browsing. In addition to the laptop computer 1011, tablet computer 1012 or mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer and a desktop computer, etc.

[0052] The server 103 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal device 101 .

[0053] It should be noted that the application file management method provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the application file management device is generally set in the server / terminal device.

[0054] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0055] Continue to refer Figure 2 , shows a flow chart of an embodiment of the application file management method according to the present application. The application file management method includes: step S201, step S202, step S203, step S204 and step S205.

[0056] In step S201, when it is detected that a new application is started, an integrity check operation is performed on the current application file of the new application to obtain an integrity check result.

[0057] In an embodiment of the present application, the new application may be a financial management application related to a financial institution (such as a bank, etc.), and the new application may also be a medical application related to a medical scenario. As an example, it may be an application for implementing functions such as personal health record management, prescription review, and examination report review. It should be understood that the examples of applications given here are only for the convenience of understanding and are not used to limit this application.

[0058] In an embodiment of the present application, when a new application is started, the system will actively detect the integrity of its files (to prevent the files from being tampered with or damaged).

[0059] In an embodiment of the present application, the present application can monitor whether a new application is started through system hooks, process monitoring or user-initiated technical means. When a new application is detected to be started, the system will intercept the startup request and perform integrity detection instead.

[0060] In the embodiment of the present application, the integrity check operation can be implemented by hash verification, digital signature verification, file size and timestamp verification, specifically:

[0061] Hash verification: Calculate the hash value (such as SHA-256) of the application file (such as executable files, dynamic libraries, configuration files, etc.) and compare it with the pre-stored benchmark hash value;

[0062] Example: If the base hash of the application file app.exe is abc123..., and the current calculated value is xyz456..., it is considered abnormal;

[0063] Digital signature verification: Checks whether the file is signed by a trusted developer and that the signature has not expired or been revoked;

[0064] File size and timestamp: Assists in verifying whether the file has been tampered with (such as abnormal file size or sudden modification time changes).

[0065] In the embodiment of the present application, after the integrity monitoring operation is completed, an integrity detection report will be generated to mark whether the file has passed the detection (such as PASS or FAIL).

[0066] Compared with the existing technology, this application can not only effectively prevent attackers from maliciously tampering with application files by modifying them and injecting malicious code (such as viruses, backdoors) by performing integrity detection operations on application files, but also avoid file damage that may be caused by storage medium failure, network transmission errors or user misoperation.

[0067] In step S202, it is determined whether there is any abnormality in the integrity detection result.

[0068] In step S203, if there is no abnormality in the integrity check result, the new application is run.

[0069] In the embodiment of the present application, if all file hash values, signatures, and structures meet expectations, the detection is confirmed to have passed and the application can be run directly.

[0070] In step S204, if the integrity check result is abnormal, a file repair operation is performed on the current application file according to the CDN technology to obtain a complete application file corresponding to the new application program.

[0071] In an embodiment of the present application, if the detection fails, the file is dynamically repaired through the CDN (Content Delivery Network) to ensure that the application is started in a complete state.

[0072] In the embodiment of the present application, the confirmation method of the integrity test result being abnormal can be:

[0073] The hash values ​​do not match (the file has been tampered with or damaged);

[0074] Digital signature verification failed (file source is untrusted);

[0075] Key files are missing (for example, some files are deleted by mistake).

[0076] In the embodiment of the present application, the implementation method of performing the file repair operation on the current application file based on the CDN technology may be:

[0077] 1) Locate the problem file: Based on the integrity check report, determine which files failed the check (such as app.exe or conf.exe).

[0078] 2) Get the complete file through CDN:

[0079] CDN's role: CDN nodes store the latest complete version of the application (or verified benchmark files);

[0080] Request repair: The system initiates a request to the CDN to obtain the latest copy of the problem file (or a baseline file with a matching hash);

[0081] As an example: if app.exe is corrupted, download the latest version of the file (e.g. app_v1.2.exe) from the CDN.

[0082] 3) Replace local files: Replace the damaged or tampered local files with the complete files returned by the CDN.

[0083] Compared with the existing technology, this application utilizes the global distribution characteristics of CDN nodes to download files from the nearest node, reducing latency and quickly obtaining complete files; in addition, repair requests are processed by CDN instead of directly accessing the source server, avoiding overload of the source station and effectively reducing the pressure on the source station; CDN can store multiple versions of the application and support rollback to historical versions (if there are still problems after the repair), effectively performing version control.

[0084] In step S205 , the new application program is run according to the complete application file.

[0085] In an embodiment of the present application, after completing the operation of replacing the local file, the integrity of the repaired file can be checked again to ensure that the repair is successful.

[0086] In the embodiment of the present application, the application is started using the repaired complete file.

[0087] In actual applications, suppose a user double-clicks to start enterprise office software, and the system finds that the hash value of office.exe does not match the benchmark (may be tampered with by a virus), the system will download the latest version of office.exe from the CDN, replace the local file and re-verify it. For the user, the user may see a brief "Repairing" prompt, and then the software starts normally.

[0088] In an embodiment of the present application, a method for managing application files is provided, comprising: when a new application is detected to be launched, performing an integrity check on the current application file of the new application to obtain an integrity check result; determining whether the integrity check result contains any anomalies; if the integrity check result contains no anomalies, running the new application; if the integrity check result contains no anomalies, performing a file repair operation on the current application file based on CDN technology to obtain a complete application file corresponding to the new application; and running the new application based on the complete application file. Compared with the prior art, the present application achieves secure startup and rapid recovery of applications through the combination of integrity checking and CDN repair, significantly reducing startup failures or security risks caused by file issues.

[0089] In some optional implementations of the embodiments of the present application, the step of performing an integrity check on the current application file of the new application upon detecting the startup of the new application to obtain an integrity check result specifically includes the following steps:

[0090] The trained anomaly recognition model is called, and the current application file of the new application is input into the trained anomaly recognition model to perform an anomaly recognition operation to obtain an integrity detection result.

[0091] In the embodiment of the present application, the anomaly recognition model may be a supervised learning model. Specifically, the anomaly recognition model may be:

[0092] Decision tree-based anomaly identification model: A decision tree can be constructed based on various characteristics of application files (such as file size, modification time, hash value, etc.) to classify whether the file is abnormal. The decision tree model is simple to understand and highly interpretable, and can quickly judge new files;

[0093] Anomaly recognition model based on support vector machines (SVM): This model finds the optimal hyperplane in high-dimensional space to separate normal and abnormal files, achieving good classification results even for small sample sizes. This model is suitable for applications with high-dimensional file features and relatively small sample sizes.

[0094] Neural network-based anomaly recognition models, such as the Multilayer Perceptron (MLP), can handle complex nonlinear relationships and more accurately identify file anomalies. However, they require large amounts of training data and computing resources, and the models lack interpretability.

[0095] In the embodiment of the present application, the anomaly recognition model may also be an unsupervised learning model. Specifically, the anomaly recognition model may be:

[0096] Anomaly identification models based on clustering algorithms (such as K-Means): Application files can be clustered according to their characteristics, and files that deviate from normal clusters are considered abnormal files. This is suitable for identifying anomalies by discovering natural groupings in the data when there is no clear abnormality label data.

[0097] Isolation Forest-based anomaly recognition model: An algorithm specifically used for anomaly detection that "isolates" outliers by randomly selecting features and segmentation values, effectively detecting anomalies in data.

[0098] Compared with the existing technology, this application uses a learning model to analyze the historical integrity detection results and related features of the application, learn the patterns of normal and abnormal files, and thus more accurately determine whether new application files have abnormalities, rather than relying solely on simple hash comparisons.

[0099] In some optional implementations of the embodiments of the present application, before the step of inputting the current application file of the new application into the trained anomaly recognition model for anomaly recognition operation to obtain the integrity test result, the following steps are also included:

[0100] Obtain historical integrity check results corresponding to the new application;

[0101] An initial anomaly recognition model is constructed, and a model training operation is performed on the anomaly recognition model according to the historical integrity detection results to obtain a trained anomaly recognition model.

[0102] Compared with the existing technology, the present application can train an anomaly recognition model that can accurately determine whether a new application file has an anomaly.

[0103] In some optional implementations of the embodiments of the present application, if the integrity check result is abnormal, the step of performing a file repair operation on the current application file based on CDN technology to obtain a complete application file corresponding to the new application program specifically includes the following steps:

[0104] Determine the abnormal type of the application file based on the integrity test results;

[0105] Call the trained repair strategy recognition model and input the abnormal type data into the repair strategy recognition model to perform repair strategy recognition operations and obtain the CDN repair strategy;

[0106] Perform file repair operations on the current application file according to the CDN repair strategy to obtain the complete application file.

[0107] In the embodiment of the present application, the repair strategy identification model may be:

[0108] Decision tree-based repair strategy identification model: The decision tree model can classify repair strategies based on different characteristics, making it easy to understand and explain. For example, a decision tree can be built based on characteristics such as file size and anomaly type to determine which CDN node to obtain the file from.

[0109] Random forest-based restoration strategy identification model: Random forest is an integrated model of decision trees. By building multiple decision trees and combining their prediction results, the accuracy and stability of the model can be improved. It can handle high-dimensional data and nonlinear relationships between features.

[0110] Repair strategy identification model based on gradient boosted decision tree (GBDT): GBDT is also an ensemble learning algorithm that builds a decision tree by gradually optimizing a loss function. It performs well in many practical problems. It is robust to outliers and can capture complex patterns in the data.

[0111] Neural network-based repair strategy identification model: For complex data relationships, neural network models such as multi-layer perceptrons (MLPs) and convolutional neural networks (CNNs, if the features have spatial structure) can be used. Neural networks have powerful learning capabilities, but require large amounts of data for training and have poor model interpretability.

[0112] Compared with the existing technology, this application classifies and analyzes different abnormal situations based on the learning model, selects the optimal CDN repair strategy, such as which CDN node to obtain the file from, the version of the file to obtain, etc., to improve the repair efficiency and accuracy.

[0113] In some optional implementations of the embodiments of the present application, before the step of calling the trained repair strategy identification model and inputting the abnormality type data into the repair strategy identification model to perform a repair strategy identification operation to obtain the CDN repair strategy, the following steps are also included:

[0114] Read the system database to obtain abnormal file data, repair operation data, and CDN node information that occurred in historical applications;

[0115] Perform key feature extraction on abnormal file data, repair operation data, and CDN node information to obtain target key feature extraction results;

[0116] An initialization repair strategy recognition model is constructed, and a model training operation is performed on the initialization repair strategy recognition model according to the target key feature extraction result to obtain a trained repair strategy recognition model.

[0117] In the embodiment of the present application, first, relevant data needs to be collected. The relevant data includes abnormal file data, repair operation data, and CDN node information. Specifically:

[0118] Abnormal file data: Collects file information from past application anomalies, including file size, modification time, hash value, anomaly type (such as file corruption, tampering, etc.), the time and environment of the anomaly (such as operating system version, network status, etc.). This data can be obtained from the system integrity detection log and application operation log;

[0119] Repair operation data: records the strategy adopted each time an abnormal file is repaired, such as which CDN node the file was obtained from, the file version obtained, the time taken to repair, etc. At the same time, records the results of the repair, such as whether the file was successfully repaired and whether the application can run normally after the repair.

[0120] CDN node information: Collect relevant information about CDN nodes, such as the node's geographical location, network bandwidth, file update frequency, historical response time, etc. This information can help the model understand the performance and reliability of different nodes.

[0121] In the embodiment of the present application, after collecting relevant data, key features need to be extracted, specifically:

[0122] File characteristics: including file size, modification time, hash value changes (differences from the original file's hash value), file type, etc. For example, if the file size is significantly different from the normal version, it may mean that the file has been tampered with;

[0123] Environmental characteristics: such as operating system version, application version, network conditions (such as bandwidth, latency), etc. Different operating systems and application versions may have different requirements for file repair, and network conditions can also affect the speed of obtaining files from CDN nodes;

[0124] Historical repair features: These include the success rate and repair time of repairing the file from different CDN nodes in the past. These features can help the model learn which CDN nodes are more reliable in specific situations.

[0125] In the embodiment of the present application, after extracting the key features, the model training operation is started, specifically:

[0126] Initialize model parameters: Initialize the model parameters according to the selected model type. For example, for a neural network model, initialize the weights and biases;

[0127] Forward propagation: input the feature data in the training set into the model and calculate the model's prediction results;

[0128] Calculate the loss function: Based on the model's predictions and the true repair strategy labels, calculate the loss function. The loss function measures the difference between the model's predictions and the true results.

[0129] Backpropagation and parameter update: The gradient of the loss function with respect to the model parameters is calculated through the backpropagation algorithm, and then the optimization algorithm (such as stochastic gradient descent, Adam, etc.) is used to update the model parameters so that the value of the loss function gradually decreases;

[0130] Repeated iteration: Repeat the process of forward propagation, loss function calculation, backpropagation, and parameter update until the performance of the model on the validation set no longer improves significantly or reaches the preset number of iterations.

[0131] Compared with the existing technology, the present application can train a repair strategy identification model to select the optimal CDN repair strategy.

[0132] In some optional implementations of the embodiments of the present application, the step of performing a key feature extraction operation on the abnormal file data, the repair operation data, and the CDN node information to obtain a target key feature extraction result specifically includes the following steps:

[0133] Perform key feature extraction on abnormal file data, repair operation data, and CDN node information to obtain initial key feature extraction results;

[0134] The initial key feature extraction results are screened according to the feature selection algorithm to obtain the target key feature extraction results that have the greatest impact on the optimization of the repair strategy.

[0135] Compared with existing technologies, this application uses feature selection algorithms (such as chi-square test, mutual information, recursive feature elimination, etc.) to select the features that are most influential in optimizing the repair strategy. This removes redundant and irrelevant features, reduces the complexity of the model, and improves the training efficiency and generalization ability of the model.

[0136] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0137] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0138] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware via computer-readable instructions. The computer-readable instructions can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes in the above-described method embodiments. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0139] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified 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 of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0140] Further references Figure 3 , as a response to the above Figure 2 The present application provides an embodiment of an application file management device. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0141] like Figure 3 As shown, the application file management device 200 of the embodiment of the present application includes:

[0142] The integrity detection module 210 is used to perform an integrity detection operation on the current application file of the new application when a new application is detected to be started, and obtain an integrity detection result;

[0143] Anomaly determination module 220, used to determine whether there is an anomaly in the integrity detection result;

[0144] A first detection result module 230 is configured to run a new application if the integrity detection result does not contain any abnormality;

[0145] The second detection result module 240 is configured to perform a file repair operation on the current application file according to the CDN technology to obtain a complete application file corresponding to the new application program if the integrity detection result is abnormal;

[0146] The program running module 250 is used to run the new application program according to the complete application file.

[0147] In an embodiment of the present application, an application file management device 200 is provided, comprising: an integrity detection module 210, for performing an integrity detection operation on the current application file of the new application when a new application is detected to be started, and obtaining an integrity detection result; an abnormality judgment module 220, for judging whether there is an abnormality in the integrity detection result; a first detection result module 230, for running the new application if there is no abnormality in the integrity detection result; a second detection result module 240, for performing a file repair operation on the current application file according to CDN technology if the integrity detection result is abnormal, and obtaining a complete application file corresponding to the new application; and a program running module 250, for running the new application based on the complete application file. Compared with the prior art, the present application achieves safe startup and rapid recovery of the application through the combination of integrity detection and CDN repair, significantly reducing startup failures or security risks caused by file problems.

[0148] In some optional implementations of the embodiments of the present application, the integrity detection module includes:

[0149] The integrity detection submodule is used to call the trained anomaly recognition model and input the current application file of the new application into the trained anomaly recognition model to perform an anomaly recognition operation and obtain an integrity detection result.

[0150] In some optional implementations of the embodiments of the present application, the application file management device 200 further includes:

[0151] A historical detection result acquisition module is used to obtain historical integrity detection results corresponding to the new application;

[0152] The anomaly recognition model training module is used to construct an initialized anomaly recognition model and perform model training operations on the anomaly recognition model based on historical integrity detection results to obtain a trained anomaly recognition model.

[0153] In some optional implementations of the embodiments of the present application, the second detection result module includes:

[0154] An exception type confirmation unit, used to confirm the exception type of the application file based on the integrity detection result;

[0155] The repair strategy identification unit is used to call the trained repair strategy identification model and input the abnormality type data into the repair strategy identification model to perform a repair strategy identification operation to obtain the CDN repair strategy;

[0156] The file repair unit is used to perform a file repair operation on the current application file according to the CDN repair strategy to obtain a complete application file.

[0157] In some optional implementations of the embodiments of the present application, the application file management device 200 further includes:

[0158] The historical repair data acquisition module is used to read the system database and obtain abnormal file data, repair operation data and CDN node information of historical applications in the system database;

[0159] The key feature extraction module is used to perform key feature extraction operations on abnormal file data, repair operation data, and CDN node information to obtain target key feature extraction results;

[0160] The repair strategy identification model training module is used to construct an initialization repair strategy identification model and perform model training operations on the initialization repair strategy identification model according to the target key feature extraction results to obtain a trained repair strategy identification model.

[0161] In some optional implementations of the embodiments of the present application, the key feature extraction module includes:

[0162] The key feature extraction submodule is used to perform key feature extraction operations on abnormal file data, repair operation data, and CDN node information to obtain initial key feature extraction results;

[0163] The feature screening submodule is used to perform feature screening operations on the initial key feature extraction results according to the feature selection algorithm to obtain the target key feature extraction results that have the greatest impact on the optimization of the repair strategy.

[0164] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4This is a basic structural block diagram of the computer device according to an embodiment of the present application.

[0165] The computer device 300 includes a memory 310, a processor 320, and a network interface 330 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 300 having components 310-330, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0166] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0167] The memory 310 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic storage, magnetic disk, optical disk, etc. In some embodiments, the memory 310 may be an internal storage unit of the computer device 300, such as a hard disk or memory of the computer device 300. In other embodiments, the memory 310 may also be an external storage device of the computer device 300, such as a plug-in hard disk equipped on the computer device 300, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 310 may also include both the internal storage unit of the computer device 300 and its external storage device. In the embodiment of the present application, the memory 310 is generally used to store the operating system and various application software installed on the computer device 300, such as computer-readable instructions for application file management methods. In addition, the memory 310 can also be used to temporarily store various data that has been output or is about to be output.

[0168] In some embodiments, the processor 320 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 320 is generally used to control the overall operation of the computer device 300. In the embodiment of the present application, the processor 320 is used to execute computer-readable instructions stored in the memory 310 or process data, such as computer-readable instructions for executing the application file management method.

[0169] The network interface 330 may include a wireless network interface or a wired network interface. The network interface 330 is generally used to establish a communication connection between the computer device 300 and other electronic devices.

[0170] The computer device provided in this application achieves safe startup and rapid recovery of applications through a combination of integrity detection and CDN repair, significantly reducing startup failures or security risks caused by file problems.

[0171] The present application also provides another embodiment, namely, providing a computer-readable storage medium, which stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the application file management method as described above.

[0172] The computer-readable storage medium provided in this application achieves secure startup and rapid recovery of applications through a combination of integrity detection and CDN repair, significantly reducing startup failures or security risks caused by file problems.

[0173] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0174] Obviously, the embodiments described above are only some of the embodiments of the present application, rather than all of the embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned specific embodiments, or to make equivalent replacements for some of the technical features therein. Any equivalent structure made using the contents of the present application specification and the accompanying drawings, directly or indirectly used in other related technical fields, is also within the scope of patent protection of the present application.

Claims

1. A method for managing application files, characterized in that: The method is applied to a computer terminal and comprises the following steps: When a new application is detected to be started, an integrity check operation is performed on the current application file of the new application to obtain an integrity check result; Determining whether the integrity test result is abnormal; If there is no abnormality in the integrity check result, running the new application; If the integrity check result is abnormal, performing a file repair operation on the current application file according to CDN technology to obtain a complete application file corresponding to the new application; The new application program is run according to the complete application file.

2. The application file management method according to claim 1, characterized in that: The step of performing an integrity check operation on the current application file of the new application when a new application is detected to be started and obtaining an integrity check result specifically includes the following steps: The trained anomaly recognition model is called, and the current application file of the new application is input into the trained anomaly recognition model to perform an anomaly recognition operation to obtain the integrity detection result.

3. The application file management method according to claim 2, characterized in that: Before the step of inputting the current application file of the new application into the trained anomaly recognition model to perform an anomaly recognition operation and obtain the integrity detection result, the following step is also included: Obtaining a historical integrity check result corresponding to the new application; An initialization anomaly recognition model is constructed, and a model training operation is performed on the anomaly recognition model according to the historical integrity detection result to obtain the trained anomaly recognition model.

4. The application file management method according to claim 1, characterized in that: If the integrity check result is abnormal, performing a file repair operation on the current application file according to CDN technology to obtain a complete application file corresponding to the new application program specifically includes the following steps: Determining the abnormal type of the application file according to the integrity detection result; Calling a trained repair strategy identification model, and inputting the abnormality type data into the repair strategy identification model to perform a repair strategy identification operation to obtain a CDN repair strategy; Perform a file repair operation on the current application file according to the CDN repair strategy to obtain the complete application file.

5. The application file management method according to claim 4, characterized in that: Before the step of calling the trained repair strategy identification model and inputting the abnormality type data into the repair strategy identification model to perform a repair strategy identification operation to obtain the CDN repair strategy, the following step is also included: Reading a system database, and obtaining abnormal file data, repair operation data, and CDN node information that occurred in historical applications from the system database; Performing a key feature extraction operation on the abnormal file data, the repair operation data, and the CDN node information to obtain a target key feature extraction result; An initialization repair strategy identification model is constructed, and a model training operation is performed on the initialization repair strategy identification model according to the target key feature extraction result to obtain the trained repair strategy identification model.

6. The application file management method according to claim 5, characterized in that: The step of performing a key feature extraction operation on the abnormal file data, the repair operation data, and the CDN node information to obtain a target key feature extraction result specifically includes the following steps: Performing a key feature extraction operation on the abnormal file data, the repair operation data, and the CDN node information to obtain an initial key feature extraction result; A feature screening operation is performed on the initial key feature extraction result according to a feature selection algorithm to obtain the target key feature extraction result that has the greatest impact on the optimization of the repair strategy.

7. An application file management device, characterized in that: include: The integrity detection module is used to perform an integrity detection operation on the current application file of the new application when a new application is detected to be started, and obtain an integrity detection result; An abnormality judgment module, used to judge whether there is an abnormality in the integrity detection result; A first detection result module, configured to run the new application if there is no abnormality in the integrity detection result; a second detection result module, configured to, if the integrity detection result is abnormal, perform a file repair operation on the current application file according to CDN technology to obtain a complete application file corresponding to the new application; A program running module is used to run the new application program according to the complete application file.

8. The application file management device according to claim 7, characterized in that: The integrity detection module includes: The integrity detection submodule is used to call the trained exception recognition model and input the current application file of the new application into the trained exception recognition model to perform an exception recognition operation to obtain the integrity detection result.

9. A computer device comprising a memory and a processor, characterized in that: The memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, the steps of the application file management method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the application file management method according to any one of claims 1 to 6.

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