Autonomous method, device and storage medium for expanding dynamic library based on browser plug-in

Abstract

The present application relates to an autonomous method, device, and storage medium for expanding dynamic libraries based on browser plug-ins, and to the field of computer technology. The method includes obtaining the website where each browser plug-in is clicked and used within a preset time period, the number of times it is used on each website, and the log of each existing application component in each browser plug-in, determining the busyness of the browser plug-in based on the website and the number of times it is used, determining the abnormal log of each existing application component in the browser plug-in and the first proportion of the abnormal log, judging whether there is an abnormal application component that needs to be updated in the browser plug-in based on the abnormal log and the first proportion, determining the abnormal level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component, and determining the update priority of each abnormal application component based on the abnormal level. The present application can make the update and repair of multiple existing application components more orderly, so as to reduce the impact on the update task and the normal operation of the browser plug-in.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an autonomous method, device, and storage medium for expanding a dynamic library based on a browser plug-in. Background Art

[0002] In the browser scenario, in order to expand the functions of the browser, such as blocking advertisements, a browser plug-in is usually installed and embedded in the browser. The browser plug-in consists of multiple application components that can achieve different functions and effects. Different browser plug-ins can achieve different functions, but the same application components may exist in different browser plug-ins. Dynamic link library technology is then applied to browser plug-ins.

[0003] Split the browser plug-in into multiple components, separate component boundaries and responsibilities, develop a variety of function-specific components, and then combine them into various complex browser plug-ins as needed. This kind of component is organized in the form of a dynamic link library and embedded in various host applications in operating system terminals such as Windows and Linux. It is called an application component.

[0004] An application component can be a COM component written in accordance with a certain specification of the application program interface, which can be reused by multiple browser plug-ins to facilitate the upgrade and expansion of browser plug-ins. As the scenarios and requirements change more and more, there are more and more browser plug-ins and application components. When multiple existing application components are abnormal, due to the differences in the application scenarios and application websites of the browser plug-ins where the application components are located, if multiple existing application components are updated at the same time, it may cause the update task to be stuck and slow, and then the normal operation of more important browser plug-ins may be affected for a long time while updating at the same time. Therefore, how to update and repair multiple existing application components in an orderly manner becomes a problem. Summary of the invention

[0005] In order to make the update and repair of multiple existing application components more orderly and reduce the impact on the update tasks and the normal operation of the browser plug-in, the present application provides an autonomous method, device, and storage medium for expanding dynamic libraries based on browser plug-ins.

[0006] In the first aspect, the present application provides an autonomous method for expanding dynamic libraries based on browser plug-ins, which adopts the following technical solutions:

[0007] The autonomous method of expanding dynamic libraries based on browser plug-ins includes:

[0008] Obtain the websites where each browser plug-in is clicked and used within a preset time period, the number of times it is used on each website, and the logs of each existing application component in each browser plug-in;

[0009] Determine the busyness of each browser plug-in based on the website and the number of times it is used;

[0010] Determine the exception logs of each existing application component in each browser plug-in and the first percentage of the exception logs;

[0011] Based on the exception log and the first ratio, determining whether there is an abnormal application component in each browser plug-in that needs to be updated;

[0012] If there is an abnormal application component, determining the abnormal level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component;

[0013] An update priority of each abnormal application component is determined based on the abnormality level.

[0014] By adopting the above technical solution, each browser plug-in can be applied to different websites. Therefore, the website where each browser plug-in is clicked and used is obtained, and the number of times it is used on each website is obtained. The browser plug-in is composed of multiple application components. Each application component generates a log during operation. The log of each application component is also obtained. Since the websites corresponding to the browser plug-ins are different, the number of times they are used on each website is also different. Therefore, the busyness of each browser plug-in is determined according to the website and the number of times they are used. The higher the busyness, the more important the browser plug-in is. Since there are various abnormal logs, according to the abnormal logs of the existing application components in each browser plug-in and the first proportion of the abnormal logs, it is determined whether there are abnormal application components that need to be updated in the browser plug-in. The busyness and abnormal logs are both key factors that affect the abnormal level of the abnormal application component. Therefore, the abnormal level of each abnormal application component is determined according to the busyness and the abnormal log, and finally the priority of each abnormal application component is determined according to the abnormal level, so that the update of the abnormal application component is more orderly. Updating the abnormal application component with high priority first can reduce the impact on the normal operation of the browser plug-in.

[0015] In another possible implementation, each browser plug-in has a corresponding click time when it is clicked and used, and the busyness of each browser plug-in is determined based on the website and the number of times it is used, including:

[0016] Obtain the number of visits to each website within the preset time period;

[0017] Determine a first number of concentrated click time periods for each browser plug-in based on the click time;

[0018] Determine a second number of the websites, and sum the usage times on each website to obtain a total number of times;

[0019] A first score for each browser plug-in is determined based on the number of visits, the first number, the second number, the total number of times, and respective corresponding coefficients, where the first score represents the busyness.

[0020] In another possible implementation, judging whether there is an abnormal application component that needs to be updated in each browser plug-in based on the abnormal log and the first ratio includes:

[0021] Determine the exception type of each existing application component's exception log, and each exception type corresponds to a threat level;

[0022] Determine the target anomaly type whose threat level reaches the preset threat level, and determine the total number of anomaly logs of all target anomaly types;

[0023] Determine a second ratio of the sum of the number of abnormal logs to the number of all abnormal logs;

[0024] If there is a target abnormal type whose second proportion reaches the preset proportion, each of the existing application components is determined to be the abnormal application component that needs to be updated.

[0025] In another possible implementation, the determining the abnormality level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component includes:

[0026] determining a third number of exception types of the exception log of each abnormal application component;

[0027] Determining an average threat level of all anomaly types and a third ratio of the number of the target anomaly type to the third number;

[0028] Determine a second score based on the busyness, the third number, the first proportion, the second proportion, the third proportion, and respective corresponding coefficients;

[0029] The abnormality level of each abnormal application component is determined based on the second score and the target browser plug-in.

[0030] In another possible implementation, determining the abnormality level of each abnormal application component based on the second score and the target browser plug-in includes:

[0031] determining a fourth number of target browser plug-ins corresponding to each abnormal application component;

[0032] Determine an average busyness based on the busyness of the target browser plug-in;

[0033] Modifying the second score of each abnormal application component based on the fourth number and the average busyness to obtain a final score;

[0034] Determining a target score interval in which the final score is located from a plurality of preset score intervals, each preset score interval corresponding to a preset abnormality level;

[0035] The preset abnormality level corresponding to the target score interval is determined as the abnormality level of each abnormal application component.

[0036] In another possible implementation, the method further includes:

[0037] When a new website is obtained, access the new website and obtain a screen in the new website;

[0038] Recognize the text in the picture to obtain the text information in the picture;

[0039] Performing semantic recognition on the text information to obtain the semantics of the text information, wherein each browser plug-in corresponds to a preset semantics;

[0040] Determining an associated browser plug-in based on the semantics and preset semantics of each browser plug-in;

[0041] The associated browser plug-in is determined as the browser plug-in of the new website.

[0042] In another possible implementation, each application component has a corresponding name identifier, and the method further includes:

[0043] The name identification and abnormal level of the abnormal application component are sent to the terminal device of the administrator.

[0044] In the second aspect, the present application provides an autonomous device for expanding dynamic libraries based on browser plug-ins, which adopts the following technical solutions:

[0045] An autonomous device based on a browser plug-in that extends the dynamic library, including:

[0046] A data acquisition module is used to obtain the websites where each browser plug-in is clicked and used within a preset time period, the number of times it is used on each website, and the logs of each existing application component in each browser plug-in;

[0047] A first determination module, used to determine the busyness of each browser plug-in based on the website and the number of times it is used;

[0048] A second determination module is used to determine the abnormal log of each existing application component in each browser plug-in and a first proportion of the abnormal log;

[0049] A judgment module, used for judging whether there is an abnormal application component that needs to be updated in each browser plug-in based on the abnormal log and the first ratio;

[0050] A level determination module, for determining the abnormal level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component when there is an abnormal application component;

[0051] The priority determination module is used to determine the update priority of each abnormal application component based on the abnormal level.

[0052] By adopting the above technical solution, each browser plug-in can be applied to different websites. Therefore, the data acquisition module acquires the website where each browser plug-in is clicked and used, and acquires the number of times it is used on each website. The browser plug-in is composed of multiple application components. Each application component generates a log during operation. The log of each application component is also acquired. Since the websites corresponding to the browser plug-ins are different, the number of times they are used on each website is also different. Therefore, the first determination module determines the busyness of each browser plug-in according to the website and the number of times they are used. The higher the busyness, the more important the browser plug-in is. Since there are various abnormal logs, the second determination module determines the abnormal logs of the existing application components in each browser plug-in and the first proportion of the abnormal logs, and then the judgment module determines whether there are abnormal application components that need to be updated in the browser plug-in. The busyness and the abnormal log are both key factors affecting the abnormal level of the abnormal application component. Therefore, the level determination module determines the abnormal level of each abnormal application component according to the busyness and the abnormal log. Finally, the priority determination module determines the priority of each abnormal application component according to the abnormal level, so that the update of the abnormal application component is more orderly. Updating the abnormal application component with high priority first can reduce the impact on the normal operation of the browser plug-in.

[0053] In another possible implementation, each browser plug-in has a corresponding click time when it is clicked and used, and the first determination module, when determining the busyness of each browser plug-in based on the website and the number of times of use, is specifically used to:

[0054] Obtain the number of visits to each website within the preset time period;

[0055] Determine a first number of concentrated click time periods for each browser plug-in based on the click time;

[0056] Determine a second number of the websites, and sum the usage times on each website to obtain a total number of times;

[0057] A first score for each browser plug-in is determined based on the number of visits, the first number, the second number, the total number of times, and respective corresponding coefficients, where the first score represents the busyness.

[0058] In another possible implementation, when the judgment module judges whether there is an abnormal application component that needs to be updated in each browser plug-in based on the abnormal log and the first ratio, it is specifically used to:

[0059] Determine the exception type of each existing application component's exception log, and each exception type corresponds to a threat level;

[0060] Determine the target anomaly type whose threat level reaches the preset threat level, and determine the total number of anomaly logs of all target anomaly types;

[0061] Determine a second ratio of the sum of the number of abnormal logs to the number of all abnormal logs;

[0062] If there is a target abnormal type whose second proportion reaches the preset proportion, each of the existing application components is determined to be the abnormal application component that needs to be updated.

[0063] In another possible implementation, when the level determination module determines the abnormal level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component, it is specifically used to:

[0064] determining a third number of exception types of the exception log of each abnormal application component;

[0065] Determining an average threat level of all anomaly types and a third ratio of the number of the target anomaly type to the third number;

[0066] Determine a second score based on the busyness, the third number, the first proportion, the second proportion, the third proportion, and respective corresponding coefficients;

[0067] The abnormality level of each abnormal application component is determined based on the second score and the target browser plug-in.

[0068] In another possible implementation, when the level determination module determines the abnormal level of each abnormal application component based on the second score and the target browser plug-in, it is specifically configured to:

[0069] determining a fourth number of target browser plug-ins corresponding to each abnormal application component;

[0070] Determine an average busyness based on the busyness of the target browser plug-in;

[0071] Modifying the second score of each abnormal application component based on the fourth number and the average busyness to obtain a final score;

[0072] Determining a target score interval in which the final score is located from a plurality of preset score intervals, each preset score interval corresponding to a preset abnormality level;

[0073] The preset abnormality level corresponding to the target score interval is determined as the abnormality level of each abnormal application component.

[0074] In another possible implementation, the device further includes:

[0075] A screen acquisition module, used for accessing a new website and acquiring the screen in the new website when a new website is acquired;

[0076] A text recognition module is used to recognize the text in the picture and obtain the text information in the picture;

[0077] A semantic recognition module, used for performing semantic recognition on the text information to obtain the semantics of the text information, wherein each browser plug-in corresponds to a preset semantics;

[0078] A third determination module, configured to determine an associated browser plug-in based on the semantics and preset semantics of each browser plug-in;

[0079] The fourth determining module is used to determine the associated browser plug-in as the browser plug-in of the new website.

[0080] In another possible implementation, each application component has a corresponding name identifier, and the device further includes:

[0081] The sending module is used to send the name identification and abnormal level of the abnormal application component to the terminal device of the administrator.

[0082] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0083] An electronic device, comprising:

[0084] at least one processor;

[0085] Memory;

[0086] At least one application, wherein at least one application is stored in a memory and configured to be executed by at least one processor, and at least one configuration is used to: execute the browser plug-in-based extended dynamic library autonomous method shown in any possible implementation of the first aspect.

[0087] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0088] A computer-readable storage medium, when the computer program is executed in a computer, enables the computer to execute the autonomous method for expanding a dynamic library based on a browser plug-in as described in any one of the first aspects.

[0089] In summary, the present application includes at least one of the following beneficial technical effects:

[0090] Each browser plug-in can be applied to different websites. Therefore, the website where each browser plug-in is clicked and used is obtained, and the number of times it is used on each website is obtained. The browser plug-in is composed of multiple application components. Each application component generates logs during operation. The logs of each application component are also obtained. Since the browser plug-ins correspond to different websites, the number of times they are used on each website is also different. Therefore, the busyness of each browser plug-in is determined according to the website and the number of times they are used. The higher the busyness, the more important the browser plug-in is. Since there are various abnormal logs, according to the abnormal logs of the existing application components in each browser plug-in and the first proportion of the abnormal logs, it is determined whether there are abnormal application components that need to be updated in the browser plug-in. The busyness and abnormal logs are both key factors affecting the abnormal level of the abnormal application component. Therefore, the abnormal level of each abnormal application component is determined according to the busyness and abnormal logs. Finally, the priority of each abnormal application component is determined according to the abnormal level, so that the update of abnormal application components is more orderly. Updating the abnormal application components with high priority first can reduce the impact on the normal operation of the browser plug-in. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] Figure 1 It is a flowchart of the autonomous method for expanding dynamic libraries based on browser plug-ins according to an embodiment of the present application.

[0092] Figure 2 It is a structural diagram of an autonomous device for expanding a dynamic library based on a browser plug-in according to an embodiment of the present application.

[0093] Figure 3 It is a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0094] The present application is further described in detail below in conjunction with the accompanying drawings.

[0095] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but such modifications are protected by patent law as long as they are within the scope of the claims of this application.

[0096] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0097] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0098] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0099] The embodiment of the present application provides an autonomous method for expanding a dynamic library based on a browser plug-in, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and the embodiment of the present application does not limit this. Figure 1 As shown, the method includes step S101, step S102, step S103, step S104, step S105 and step S106, wherein:

[0100] S101, obtaining the website on which each browser plug-in is clicked and used within a preset time period, the number of times it is used on each website, and the log of each existing application component in each browser plug-in.

[0101] For the embodiment of the present application, the preset time period can be the past seven days, the past half month, or other time periods in the past. The staff sets the preset time period through the visual operation interface and stores it in the electronic device. The electronic device is connected and communicates with each browser plug-in through a communication interface, such as an API interface. The browser plug-in is embedded in the browser and can be regarded as an application that can be used in the browser. It can be used on some websites, such as for ad blocking, translation, etc. When the browser plug-in is clicked and used on the website, the browser plug-in sends a return value to the electronic device through the API interface, so that the electronic device knows that the browser plug-in is clicked and used and the website where it is clicked and used, and counts the number of clicks and uses of each browser plug-in on each website.

[0102] S102, determining the busyness of each browser plug-in based on the website and the number of times it is used.

[0103] For the embodiments of the present application, different websites have different effects on the busyness of the browser plug-in being used. For example, the type of website (such as video websites, foreign language websites, etc.), the number of visits to the website, and the importance of the website are all factors that affect the busyness of the browser plug-in. Therefore, the relevant information and attributes of the website can reflect a certain busyness of the browser plug-in. Similarly, the number of times each browser plug-in is used on each website affects the busyness of the browser plug-in. The more times it is used, the higher the busyness of the browser plug-in. Therefore, the electronic device can accurately determine the busyness of each browser plug-in based on the website and the number of times it is used on each website.

[0104] S103: Determine the exception log of each existing application component in each browser plug-in and a first proportion of the exception log.

[0105] For the embodiments of the present application, each browser plug-in is composed of multiple application components, different application components implement different functions, and the same application components may be used in different browser plug-ins, that is, the application components are codes and data that can be used by multiple browser plug-ins. When the electronic device monitors each browser plug-in, the browser plug-in will send a log to the electronic device, and the electronic device will parse the log corresponding to each existing application component from the log, and determine the abnormal log of each existing application component. The abnormal log may include logs of situations such as long response time, function errors, and application component crashes. After the electronic device determines the abnormal log, it calculates the ratio of the number of abnormal logs of each existing application component to the total number of logs, that is, the first ratio. The larger the first ratio, the more abnormal logs there are, and the more serious the problem of the application component.

[0106] S104: Based on the abnormal log and the proportion, determine whether there is an abnormal application component in each browser plug-in that needs to be updated.

[0107] For the embodiment of the present application, since the abnormal logs include multiple types, the severity of different types of abnormal logs is different, and the abnormal logs with less severity are not enough to affect the normal operation of the application component, so the application component needs to be updated to maintain normal operation, but the proportion of abnormal logs also affects whether the application component can operate normally. If the proportion of abnormal logs is too large, the application component also needs to be updated to maintain normal operation. Therefore, the electronic device can determine whether each browser plug-in has an abnormal application component that needs to be updated based on the abnormal logs and the proportion of abnormal logs.

[0108] S105: If there is an abnormal application component, determine the abnormal level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component.

[0109] For the embodiment of the present application, if the electronic device determines that there is an abnormal application component in a certain browser plug-in, it means that the abnormal application component needs to be updated. However, in order to save computing power and make the update of the application component orderly, it is necessary to determine the abnormal level of each abnormal application component according to the busyness of the browser plug-in corresponding to the abnormal application component and the abnormal log of each abnormal application component. The higher the abnormal level, the greater the impact on the normal operation of the browser plug-in, and the more priority it needs to be updated.

[0110] S106: Determine the update priority of each abnormal application component based on the abnormality level.

[0111] For the embodiment of the present application, after the electronic device determines the abnormal level of each abnormal application component, it sorts the abnormal application components according to the abnormal level, and determines the sorting result as the update priority of the application component. After determining the priority, the electronic device can determine other versions or the latest version of each abnormal application component from the application component library, and repair and update the abnormal application component according to the update priority, or send the update priority of the abnormal application component to the management personnel or staff when there are no other versions or the latest version of the abnormal application component in the application component library, so that the relevant personnel can write the latest version of the application component according to the update priority and store it in the application component library after writing the latest version of the application component, so that the update of the abnormal application component is more orderly. This reduces the computing power, reduces the possibility of abnormalities when the browser plug-in is running, and makes the browser plug-in run more smoothly.

[0112] In a possible implementation of the embodiment of the present application, each browser plug-in has a corresponding click time when it is clicked and used. In step S102, the busyness of each browser plug-in is determined based on the website and the number of times it is used, and specifically includes step S1021 (not shown in the figure), step S1022 (not shown in the figure), step S1023 (not shown in the figure) and step S1024 (not shown in the figure), wherein:

[0113] S1021, obtaining the number of visits to each website within a preset time period.

[0114] For the embodiments of the present application. The number of visits to each website in a preset time period can be obtained by sending a data request instruction to the website background through an electronic device, so as to send the number of visits to the electronic device after the request instruction is permitted. The electronic device can also obtain the number of visits to each website through a third-party platform, and can also obtain the number of visits to each website by accessing the log of the server where each website is located. In addition, the number of visits can also be obtained by other means. The greater the number of visits to a website, the busier the website is, and the higher the busyness of the browser plug-in that is clicked and used on the website, that is, the number of visits to the website can characterize the busyness of the browser plug-in to a certain extent. In other embodiments, the importance of each website is different, and different levels are set, and the importance of each website can also be used for calculation.

[0115] S1022: Determine a first number of concentrated click time periods of each browser plug-in based on the click time.

[0116] For the embodiment of the present application, the staff can set multiple time periods and store the multiple time periods in the electronic device. For example, 24 time periods are set, and each time period is one hour according to the time distribution of 24 hours a day, and the click time corresponding to each browser plug-in is mapped in the corresponding time period. The staff can set a quantity threshold in advance. If the number of browser plug-ins clicked and used in a certain time period reaches the quantity threshold, it means that the browser plug-in is clicked and used intensively in the time period. The electronic device selects the time period in which the number of clicks and uses reaches the quantity threshold, and counts such time periods to obtain a first quantity. The larger the first quantity, the busier the browser plug-in is.

[0117] S1023, determining a second number of websites, and summing the usage times on each website to obtain a total number of times.

[0118] For the embodiment of the present application, the more websites the browser plug-in is applied to, the more widely the browser plug-in is applied, which can also represent the busyness of the browser plug-in to a certain extent. Therefore, the electronic device counts the websites that each browser plug-in has been applied to within a preset time period to obtain a second number. For each browser plug-in, the electronic device sums the number of times each browser plug-in is used on each website to obtain the total number of times the browser plug-in is used within the preset time period. The larger the total number of times, the higher the busyness of the browser plug-in.

[0119] S1024, determining a first score for each browser plug-in based on the number of visits, the first number, the second number, the total number of times, and the corresponding coefficients.

[0120] Among them, the first score represents the busyness.

[0121] For the embodiments of the present application, it can be known from the above embodiments that the number of visits to each website corresponding to the browser plug-in within a preset time period, the first number of concentrated clicks in the time period, the second number of websites to which the application is applied, and the total number of times the browser plug-in is clicked and used within the preset time period are all important factors affecting the busyness of the browser plug-in, and the degree of influence is different. Therefore, the electronic device sets different coefficients for the above factors, and then performs weighted calculation to obtain a first score for each browser plug-in. The larger the first score, the higher the busyness of the browser plug-in, that is, the first score represents the busyness of the browser plug-in. By performing weighted calculation on the above factors that are most relevant to the busyness and comprehensively determining the first score for the busyness, the determination of the busyness is made more accurate.

[0122] In a possible implementation of the embodiment of the present application, in step S104, based on the abnormal log and the first proportion, it is determined whether there is an abnormal application component that needs to be updated in each browser plug-in, specifically including step S1041 (not shown in the figure), step S1042 (not shown in the figure), step S1043 (not shown in the figure) and step S1044 (not shown in the figure), wherein:

[0123] S1041, determining the exception type of the exception log of each existing application component.

[0124] Among them, each abnormality type corresponds to a threat level.

[0125] For the embodiment of the present application, the log has a variety of different types, such as error logs, debug logs, and access logs, and the exception logs correspond to different exception types, such as calling function errors, long response time, and crashes. The staff can set the logs that belong to the exceptions and the exception types of each exception log in the electronic device in advance. After the electronic device obtains the logs of each existing application component, it is screened according to the set exception logs and exception types, so as to determine the exception logs of each existing application component and the exception type of each exception log. Different exception types correspond to different threat levels, that is, the degree of threat to the normal operation of the browser plug-in is different. Similarly, the staff can pre-set the threat level of each exception type in the electronic device. The higher the threat level, the greater the impact on the normal operation of the browser plug-in. After the electronic device determines the exception type of each exception log, the threat level of each exception type can be determined.

[0126] S1042, determining the target anomaly type whose threat level reaches the preset threat level, and determining the total number of anomaly logs of all target anomaly types.

[0127] For the embodiment of the present application, the preset threat level is set in advance by the staff, and the preset threat level serves as the demarcation point level for whether the application component is sufficient to affect the normal operation of the browser plug-in. The electronic device compares the threat level of the abnormal log with the preset threat level. If the preset threat level is reached, it means that it is sufficient to affect the normal operation of the browser plug-in. Therefore, the electronic device determines the target abnormal type that reaches the preset threat level, and sums the abnormal logs corresponding to each target abnormal type to obtain the total number of abnormal logs of the target abnormal type. The larger the sum of the number of a certain application component, the greater the possibility that the application component needs to be updated, that is, the greater the possibility that it is an abnormal application component.

[0128] S1043, determining a second ratio of the total number of abnormal logs to the number of all abnormal logs.

[0129] For the embodiment of the present application, after the electronic device determines the total number of abnormal logs of a certain application component regarding the target abnormal type, it further determines the second proportion of the number of all abnormal logs. The larger the second proportion, the larger the proportion of the number of abnormal logs of the target abnormal type, and the greater the harm of the application component to the normal operation of the browser plug-in, that is, the greater the possibility of being an abnormal application component.

[0130] S1044: If there are application components whose second proportion reaches the preset proportion, determine that the application components that reach the preset proportion are abnormal application components that need to be updated.

[0131] For the embodiment of the present application, the staff sets a preset ratio in the electronic device in advance, and the preset ratio is used as a demarcation point for whether the ratio of the number of abnormal logs of the target abnormal type is too large. The electronic device compares the second ratio of each application component with the preset ratio. If there is an application component that reaches the second ratio, it means that the application component is more harmful to the normal operation of the browser plug-in in which it is located, and needs to be updated in time, so it is determined as an abnormal application component. By determining the total number of abnormal logs of the target abnormal type and determining the second ratio of the number of abnormal logs to the total number of abnormal logs, it is more accurate to determine the abnormal application component based on the second ratio.

[0132] In a possible implementation of the embodiment of the present application, in step S105, the abnormal level of each abnormal application component is determined based on the busyness and the abnormal log of the abnormal application component, specifically including step S1051 (not shown in the figure), step S1052 (not shown in the figure), step S1053 (not shown in the figure) and step S1054 (not shown in the figure), wherein:

[0133] S1051, determining a third number of exception types of the exception log of each abnormal application component.

[0134] For the embodiment of the present application, the more abnormal types there are in the abnormal log of the abnormal application component, the more incompatible it is with the operating environment of the browser plug-in, or the abnormal application component cannot be better applied in the current environment. Therefore, the more abnormal types there are in the abnormal application component, the higher the abnormal level of the abnormal application component is to a certain extent.

[0135] S1052: Determine an average threat level of all abnormal types and a third ratio of the number of the target abnormal type to the third number.

[0136] For the embodiment of the present application, after the electronic device determines all the abnormal types of the application components, the threat level of each abnormal type can be determined, and then the average threat level of the abnormal application components is determined using the average value calculation formula. The electronic device determines the target abnormal type that reaches the preset threat level, and calculates the ratio of the total number of target abnormal types to the third number of all abnormal types, that is, the third proportion. The larger the third proportion, the more abnormal logs with higher threat levels appear in the abnormal application component, the greater the harm to the normal operation of the browser plug-in, and the higher the corresponding abnormal level.

[0137] S1053: Determine a second score based on the busyness, the third number, the first proportion, the second proportion, the third proportion, and their corresponding coefficients.

[0138] For the embodiment of the present application, the higher the busyness of the browser plug-in, the more important the browser plug-in is, the greater the impact caused by the abnormal application component in the browser plug-in, and the more it is necessary to repair and update the abnormal browser plug-in as soon as possible. Therefore, the busyness can characterize the abnormal level of the abnormal application component to a certain extent. The larger the first proportion, the larger the proportion of abnormal logs in all logs, and the higher the abnormal level of the abnormal application component. Similarly, the third number, the first proportion, the second proportion, and the third proportion are all important factors affecting the abnormal level of the abnormal application component, and the degree of influence is different. The staff can set the coefficients corresponding to the above factors in the electronic device in advance, and perform weighted calculation to obtain the second score for the abnormal application component.

[0139] S1054: Determine the abnormality level of each abnormal application component based on the second score and the target browser plug-in.

[0140] The target browser plug-in is the called browser plug-in corresponding to each abnormal application component.

[0141] For the embodiment of the present application, since the application component is universal and can be called by other browser plug-ins and used to form the structure of other browser plug-ins, other browser plug-ins can achieve the same function. This is the characteristic of the dynamic link library. The target browser plug-in corresponding to an abnormal application component also affects the abnormal level of the abnormal application component. Therefore, the application component may be applied in multiple browser plug-ins, and the electronic device can more accurately determine the abnormal level based on the second score of each abnormal application component and the target browser plug-in.

[0142] In a possible implementation of the embodiment of the present application, in step S1054, the abnormal level of each abnormal application component is determined based on the second score and the target browser plug-in, specifically including step Sa (not shown in the figure), step Sb (not shown in the figure), step Sc (not shown in the figure), step Sd (not shown in the figure) and step Se (not shown in the figure), wherein:

[0143] Sa, determine a fourth number of target browser plug-ins corresponding to each abnormal application component.

[0144] For the embodiment of the present application, the more times an abnormal application component is called by other browser plug-ins, the more general the abnormal application component is, the higher its importance is, and the corresponding abnormal level is higher. Therefore, the electronic device can analyze the other browser plug-ins called by each abnormal application component through the logs of other browser plug-ins, and then count the other browser plug-ins called to obtain the fourth number of the target browser plug-ins.

[0145] Sb, determines the average busyness based on the busyness of the target browser plug-in.

[0146] For the embodiment of the present application, after the electronic device determines the target browser plug-in of an abnormal application component, since the busyness of each browser plug-in has been obtained through the method disclosed in steps S1021 to S1024, the electronic device can directly obtain the busyness of the target browser plug-in and determine the average busyness using the average value calculation formula. The average busyness represents the overall busyness of the browser plug-in related to the abnormal application component. The higher the average busyness, the more times and frequency the target browser plug-in where the abnormal application component is located is used, the more times and frequency the abnormal application component is called, the greater the impact of the abnormal application component on the normal operation of the target browser plug-in, and the more important the abnormal application component is.

[0147] Sc, based on the fourth quantity and the average busyness, the second score of each abnormal application component is corrected to obtain a final score.

[0148] For the embodiment of the present application, in summary, the fourth number and average busyness of the target browser plug-in are both important factors affecting the abnormal level of the abnormal application component. Therefore, the electronic device can correct the second score according to the fourth number and the average busyness, so that the second score of the abnormal application component is more accurate, and thus the abnormal level is more accurate. Specifically, the staff can set different coefficients for the fourth number and the average busyness, and then the electronic device performs weighted calculation on the fourth number and the average busyness to obtain a score. The electronic device sums the score and the second score to obtain the corrected score, i.e., the final score. The final score is calculated by comprehensively judging the properties of the abnormal log of the abnormal application component itself, the browser plug-in in which it is located, and other target browser plug-ins that call the application component, so that the abnormal level is determined more accurately according to the final score.

[0149] Sd, determines the target score interval where the final score lies from a plurality of preset score intervals.

[0150] Among them, each preset score interval corresponds to a preset abnormality level.

[0151] For the embodiment of the present application, the electronic device may store multiple preset score intervals, assuming there are five, each preset score interval corresponds to a preset abnormality level. After the electronic device determines the final score, it further determines the target score interval in which the final score is located.

[0152] Se, the preset abnormality level corresponding to the target score interval is determined as the abnormality level of each abnormal application component.

[0153] For the embodiment of the present application, the preset abnormality level of each preset score interval is calculated and obtained by the staff in advance through experiments, so that the preset score interval and the corresponding preset abnormality level are more realistic and more accurate. The electronic device directly determines the preset abnormality level corresponding to the target score interval as the abnormality level of each abnormal application component.

[0154] In a possible implementation of the embodiment of the present application, step S106 further includes step S1 (not shown in the figure), step S2 (not shown in the figure), step S3 (not shown in the figure), step S4 (not shown in the figure) and step S5 (not shown in the figure), wherein:

[0155] S1, when a new website is obtained, the new website is accessed and the screen in the new website is obtained.

[0156] For the embodiment of the present application, the new website can be input into the electronic device by the staff, or can be parsed by the electronic device from the log of each browser plug-in. After obtaining the new website, the electronic device simulates access to the website through a virtual machine and takes a screenshot to obtain the screen within the website.

[0157] S2, recognizing the text in the picture to obtain the text information in the picture.

[0158] Specifically, the electronic device may obtain text information in the screen through optical character recognition (OCR) technology.

[0159] S3, performing semantic recognition on the text information to obtain the semantics of the text information.

[0160] Among them, each browser plug-in corresponds to a preset semantics.

[0161] For the embodiment of the present application, the electronic device inputs the text information into the trained network model for semantic recognition, obtains the semantics of the text information, and then obtains the type of the new website. The semantic vocabulary of each website applicable to the browser plug-in can be tagged in advance by the staff.

[0162] S4, determining the associated browser plug-in based on the semantics and the preset semantics of each browser plug-in.

[0163] S5, determining the associated browser plug-in as a browser plug-in of a new website.

[0164] For the embodiment of the present application, the electronic device matches the recognized semantics and the semantics of each browser plug-in, and finally obtains a browser plug-in that can be applied to the new website, and controls the terminal device to display the link or icon of the associated browser plug-in on the browser interface when accessing the website, thereby improving the applicability of the browser plug-in.

[0165] In a possible implementation manner of the embodiment of the present application, each application component has a corresponding name identifier, and step S105 further includes step S107 (not shown in the figure), wherein:

[0166] S107, sending the name identification and abnormal level of the abnormal application component to the terminal device of the administrator.

[0167] For the embodiment of the present application, the electronic device generates text information based on the name tag of the abnormal application component and the corresponding abnormal level, and sends the text information to the terminal device corresponding to the management personnel, so that the management personnel can know the specific situation of the abnormal application component in time.

[0168] The above-mentioned embodiment introduces the autonomous method of extending the dynamic library based on the browser plug-in from the perspective of the method flow. The following embodiment introduces the autonomous device of extending the dynamic library based on the browser plug-in from the perspective of the virtual module or virtual unit. For details, please refer to the following embodiment.

[0169] The embodiment of the present application provides an autonomous device 20 for expanding dynamic libraries based on a browser plug-in, such as Figure 2 As shown, the browser plug-in-based extended dynamic library autonomous device 20 may specifically include:

[0170] The data acquisition module 201 is used to obtain the website where each browser plug-in is clicked and used, the number of times it is used on each website, and the log of each existing application component in each browser plug-in within a preset time period;

[0171] A first determination module 202, for determining the busyness of each browser plug-in based on the website and the number of times it is used;

[0172] The second determination module 203 is used to determine the abnormal log of each existing application component in each browser plug-in and the first proportion of the abnormal log;

[0173] A determination module 204 is used to determine whether there is an abnormal application component in each browser plug-in that needs to be updated based on the abnormal log and the first ratio;

[0174] The level determination module 205 is used to determine the abnormal level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component when there is an abnormal application component;

[0175] The priority determination module 206 is used to determine the update priority of each abnormal application component based on the abnormality level.

[0176] The embodiment of the present application discloses an autonomous device 20 for expanding dynamic libraries based on browser plug-ins, wherein each browser plug-in can be applied to different websites, so the data acquisition module 201 acquires the website where each browser plug-in is clicked and used, and acquires the number of times it is used on each website. The browser plug-in is composed of multiple application components, and each application component generates a log during operation. Similarly, the log of each application component is acquired. Since the websites corresponding to the browser plug-ins are different, the number of times it is used on each website is also different. Therefore, the first determination module 202 determines the busyness of each browser plug-in according to the website and the number of times it is used. The higher the busyness, the more important the browser plug-in is. Since various abnormal logs are generated, the number of times ... Therefore, the second determination module 203 determines whether there are abnormal application components that need to be updated in the browser plug-in according to the abnormal logs of the existing application components in each browser plug-in and the first proportion of the abnormal logs, and then the judgment module 204 determines whether there are abnormal application components that need to be updated in the browser plug-in. The busyness and the abnormal logs are both key factors affecting the abnormal level of the abnormal application components. Therefore, the level determination module 205 determines the abnormal level of each abnormal application component according to the busyness and the abnormal logs. Finally, the priority determination module 206 determines the priority of each abnormal application component according to the abnormal level, so that the update of the abnormal application components is more orderly. Updating the abnormal application components with high priorities first can reduce the impact on the normal operation of the browser plug-in.

[0177] In a possible implementation of the embodiment of the present application, each browser plug-in has a corresponding click time when it is clicked and used. When the first determination module 202 determines the busyness of each browser plug-in based on the website and the number of times it is used, it is specifically used to:

[0178] Get the number of visits to each website within a preset time period;

[0179] Determine a first number of concentrated click time periods for each browser plug-in based on the click time;

[0180] Determine a second number of websites, and sum the number of times used on each website to obtain a total number of times;

[0181] A first score of each browser plug-in is determined based on the number of visits, the first number, the second number, the total number of times, and the corresponding coefficients, where the first score represents the busyness.

[0182] In a possible implementation of the embodiment of the present application, when the judgment module 204 judges whether there is an abnormal application component that needs to be updated in each browser plug-in based on the abnormal log and the first ratio, it is specifically used to:

[0183] Determine the exception type of each existing application component's exception log, and each exception type corresponds to a threat level;

[0184] Determine the target anomaly type whose threat level reaches the preset threat level, and determine the total number of anomaly logs of all target anomaly types;

[0185] Determine a second ratio of the total number of abnormal logs to the number of all abnormal logs;

[0186] If there is a target abnormal type whose second proportion reaches the preset proportion, each existing application component is determined to be an abnormal application component that needs to be updated.

[0187] In a possible implementation of the embodiment of the present application, when the level determination module 205 determines the abnormal level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component, it is specifically used to:

[0188] determining a third number of exception types of the exception log of each abnormal application component;

[0189] Determine the average threat level of all anomaly types, and the third ratio of the number of target anomaly types to the third number;

[0190] Determine a second score based on the busyness, the third quantity, the first proportion, the second proportion, the third proportion, and respective corresponding coefficients;

[0191] An abnormality level of each abnormal application component is determined based on the second score and the target browser plug-in.

[0192] In a possible implementation of the embodiment of the present application, when the level determination module 205 determines the abnormal level of each abnormal application component based on the second score and the target browser plug-in, it is specifically used to:

[0193] determining a fourth number of target browser plug-ins corresponding to each abnormal application component;

[0194] Determine an average busyness based on the busyness of the target browser plug-in;

[0195] Correcting the second score of each abnormal application component based on the fourth quantity and the average busyness to obtain a final score;

[0196] Determine a target score interval in which the final score lies from a plurality of preset score intervals, each preset score interval corresponding to a preset abnormality level;

[0197] The preset abnormality level corresponding to the target score interval is determined as the abnormality level of each abnormal application component.

[0198] In a possible implementation of the embodiment of the present application, the device 20 further includes:

[0199] The screen acquisition module is used to access the new website and acquire the screen in the new website when a new website is acquired;

[0200] A text recognition module is used to recognize the text in the picture and obtain the text information in the picture;

[0201] Semantic recognition module, used to perform semantic recognition on text information to obtain the semantics of the text information. Each browser plug-in has a preset semantics.

[0202] A third determination module, configured to determine the associated browser plug-in based on the semantics and the preset semantics of each browser plug-in;

[0203] The fourth determining module is used to determine the associated browser plug-in as a browser plug-in of a new website.

[0204] In a possible implementation of the embodiment of the present application, each application component has a corresponding name identifier, and the device 20 further includes:

[0205] The sending module is used to send the name identification and abnormal level of the abnormal application component to the terminal device of the administrator.

[0206] Technical personnel in the relevant field can clearly understand that, for the convenience and simplicity of description, the specific working process of the browser plug-in-based extended dynamic library autonomous device 20 described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0207] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 The electronic device 30 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 30 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation on the embodiments of the present application.

[0208] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0209] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but it does not mean that there is only one bus or only one type of bus.

[0210] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0211] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0212] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0213] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment. Compared with the related art, in the embodiment of the present application, each browser plug-in can be applied to different websites. Therefore, the website where each browser plug-in is clicked and used is obtained, and the number of times it is used on each website is obtained. The browser plug-in is composed of multiple application components. Each application component generates a log during operation, and the log of each application component is also obtained. Since the websites corresponding to the browser plug-ins are different, the number of times they are used on each website is also different. Therefore, the busyness of each browser plug-in is determined according to the website and the number of times they are used. The higher the busyness, the more important the browser plug-in is. Since there are various abnormal logs, according to the abnormal logs of the existing application components in each browser plug-in and the first proportion of the abnormal logs, it is determined whether there are abnormal application components that need to be updated in the browser plug-in. The busyness and abnormal logs are both key factors affecting the abnormal level of the abnormal application components. Therefore, the abnormal level of each abnormal application component is determined according to the busyness and the abnormal log, and finally the priority of each abnormal application component is determined according to the abnormal level, so that the update of the abnormal application components is more orderly. Updating the abnormal application components with high priority first can reduce the impact on the normal operation of the browser plug-in.

[0214] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence 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 a part of the steps in the flowchart 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 part of the sub-steps or stages of other steps.

[0215] The above description is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. An autonomous method for expanding dynamic libraries based on browser plug-ins, characterized in that: include: Obtain the websites where each browser plug-in is clicked and used within a preset time period, the number of times it is used on each website, and the logs of each existing application component in each browser plug-in; Determine the busyness of each browser plug-in based on the website and the number of times it is used; Determine the exception logs of each existing application component in each browser plug-in and the first percentage of the exception logs; Based on the exception log and the first ratio, determining whether there is an abnormal application component in each browser plug-in that needs to be updated; If there is an abnormal application component, determining the abnormal level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component; Determining an update priority of each abnormal application component based on the abnormality level; The step of judging whether there is an abnormal application component that needs to be updated in each browser plug-in based on the abnormal log and the first ratio includes: Determine the exception type of each existing application component's exception log, and each exception type corresponds to a threat level; Determine the target anomaly type whose threat level reaches the preset threat level, and determine the total number of anomaly logs of all target anomaly types; Determine a second ratio of the sum of the number of abnormal logs to the number of all abnormal logs; If there is a target abnormal type whose second proportion reaches the preset proportion, each of the existing application components is determined to be the abnormal application component that needs to be updated.

2. The autonomous method for expanding dynamic libraries based on browser plug-ins according to claim 1, characterized in that: Each browser plug-in has a corresponding click time when it is clicked and used. The busyness of each browser plug-in is determined based on the website and the number of times it is used, including: Obtain the number of visits to each website within the preset time period; Determine a first number of concentrated click time periods for each browser plug-in based on the click time; Determine a second number of the websites, and sum the usage times on each website to obtain a total number of times; A first score for each browser plug-in is determined based on the number of visits, the first number, the second number, the total number of times, and respective corresponding coefficients, where the first score represents the busyness.

3. The autonomous method for expanding dynamic libraries based on browser plug-ins according to claim 1, characterized in that: The determining the abnormal level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component includes: determining a third number of exception types of the exception log of each abnormal application component; Determining an average threat level of all anomaly types and a third ratio of the number of the target anomaly type to the third number; Determine a second score based on the busyness, the third number, the first proportion, the second proportion, the third proportion, and respective corresponding coefficients; The abnormality level of each abnormal application component is determined based on the second score and the target browser plug-in.

4. The autonomous method for expanding dynamic libraries based on browser plug-ins according to claim 3 is characterized in that: The determining the abnormality level of each abnormal application component based on the second score and the target browser plug-in includes: determining a fourth number of target browser plug-ins corresponding to each abnormal application component; Determine an average busyness based on the busyness of the target browser plug-in; Modifying the second score of each abnormal application component based on the fourth number and the average busyness to obtain a final score; Determining a target score interval in which the final score is located from a plurality of preset score intervals, each preset score interval corresponding to a preset abnormality level; The preset abnormality level corresponding to the target score interval is determined as the abnormality level of each abnormal application component.

5. The autonomous method for expanding dynamic libraries based on browser plug-ins according to claim 1, characterized in that: The method further comprises: When a new website is obtained, access the new website and obtain a screen in the new website; Recognize the text in the picture to obtain the text information in the picture; Performing semantic recognition on the text information to obtain the semantics of the text information, wherein each browser plug-in corresponds to a preset semantics; Determining an associated browser plug-in based on the semantics and preset semantics of each browser plug-in; The associated browser plug-in is determined as the browser plug-in of the new website.

6. The autonomous method for expanding dynamic libraries based on browser plug-ins according to claim 1, characterized in that: Each application component has a corresponding name identifier, and the method further includes: The name identification and abnormal level of the abnormal application component are sent to the terminal device of the administrator.

7. An autonomous device for expanding dynamic libraries based on browser plug-ins, characterized in that: include: A data acquisition module is used to obtain the websites where each browser plug-in is clicked and used within a preset time period, the number of times it is used on each website, and the logs of each existing application component in each browser plug-in; A first determination module, used to determine the busyness of each browser plug-in based on the website and the number of times it is used; A second determination module is used to determine the abnormal log of each existing application component in each browser plug-in and a first proportion of the abnormal log; A judgment module, used for judging whether there is an abnormal application component that needs to be updated in each browser plug-in based on the abnormal log and the first ratio; A level determination module, for determining the abnormal level of each abnormal application component based on the busyness and the abnormal log of the abnormal application component when there is an abnormal application component; a priority determination module, configured to determine an update priority of each abnormal application component based on the abnormality level; Wherein, when the judgment module judges whether there is an abnormal application component that needs to be updated in each browser plug-in based on the abnormal log and the first proportion, it is specifically used to: Determine the exception type of each existing application component's exception log, and each exception type corresponds to a threat level; Determine the target anomaly type whose threat level reaches the preset threat level, and determine the total number of anomaly logs of all target anomaly types; Determine a second ratio of the sum of the number of abnormal logs to the number of all abnormal logs; If there is a target abnormal type whose second proportion reaches the preset proportion, each of the existing application components is determined to be the abnormal application component that needs to be updated.

8. An electronic device, characterized in that: It includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in the memory and is configured to be executed by the at least one processor, and the at least one application is used to execute the browser plug-in-based extended dynamic library autonomous method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the autonomous method for expanding a dynamic library based on a browser plug-in as described in any one of claims 1 to 6.

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