Webpage processing method and device, storage medium and electronic equipment

Abstract

The embodiment of the invention discloses a webpage processing method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining a new webpage access instruction input for a browser, determining a new access webpage based on the new webpage access instruction, then obtaining the fuzzy intensity of historical webpages stored in the browser, and obtaining the fuzzy intensity of the historical webpages; determining a fuzzy intensity correction coefficient corresponding to the newly-built access webpage, and determining target webpage fuzzy intensity corresponding to the newly-built access webpage based on the historical webpage fuzzy intensity and the fuzzy intensity correction coefficient, and performing webpage fuzzy updating processing on the newly-built access webpage based on the target webpage fuzzy intensity, and displaying the newly-built access webpage after fuzzy processing. Therefore, under the condition that the user newly builds the webpage, fuzzy processing is automatically carried out on the webpage according to the fuzzy intensity of the target webpage, user operation is simplified, and webpage privacy content protection can be rapidly achieved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a web page processing method, apparatus, storage medium, and electronic device. Background Technology

[0002] With the widespread use of internet applications, browsing the web on computers in public places such as cafes, airports, conference rooms, libraries, and offices has become commonplace. However, these open environments are often crowded and involve multiple people looking at each other. When users temporarily leave their computers or need to show their screens to colleagues or clients, sensitive information on the webpage, such as personal emails, bank accounts, chat logs, pay slips, and business reports, is easily spied on or photographed by others using mobile phones. Even if users quickly switch tabs or minimize windows, the few frames of screen flickering are enough for onlookers to catch key text.

[0003] Currently, related technologies rely on users manually minimizing the screen, locking the screen, or applying privacy screen protectors to address privacy leaks. However, these manual operations are cumbersome and easily forgotten. Therefore, how to efficiently provide web page privacy protection is a pressing technical problem that needs to be solved. Summary of the Invention

[0004] This application provides a webpage processing method, apparatus, computer storage medium, and electronic device. The technical solution is as follows: In a first aspect, embodiments of this application provide a webpage processing method, the method comprising: Obtain the new webpage access instruction input into the browser, and determine the new webpage to be accessed based on the new webpage access instruction; Obtain the blur intensity of historical web pages stored in the browser, determine the blur intensity correction coefficient corresponding to the newly accessed web page, and determine the blur intensity of the target web page corresponding to the newly accessed web page based on the blur intensity of the historical web pages and the blur intensity correction coefficient. Based on the fuzziness intensity of the target webpage, the newly accessed webpage is subjected to webpage fuzziness update processing, and the newly accessed webpage after fuzziness processing is displayed.

[0005] In some possible implementations, determining the fuzziness intensity correction coefficient corresponding to the newly accessed webpage includes: Determine the spatiotemporal privacy score, task cluster fit score, and content sensitivity score corresponding to the newly created webpage; A first correction coefficient is obtained by performing linear mapping based on the spatiotemporal privacy score, a second correction coefficient is obtained by performing linear mapping based on the task cluster fit score, and a third correction coefficient is obtained by performing linear mapping based on the content sensitivity score. The fuzz intensity correction coefficient corresponding to the newly accessed webpage is determined based on the first correction coefficient, the second correction coefficient, and the third correction coefficient.

[0006] In some possible implementations, determining the spatiotemporal privacy score, task cluster fit score, and content sensitivity score corresponding to the newly accessed webpage includes: The system obtains the user's geographic location, the network environment characteristics corresponding to the newly accessed webpage, and the webpage access time of the newly accessed webpage. Based on the user's geographic location, the network environment characteristics, and the webpage access time, it determines the spatiotemporal privacy score corresponding to the newly accessed webpage. Obtain the tab task cluster corresponding to the previously visited webpage, and perform task relevance detection processing based on the newly visited webpage and the tab task cluster to obtain the task cluster matching score corresponding to the newly visited webpage. The newly created webpage is processed to identify sensitive content, resulting in a content sensitivity score.

[0007] In some possible implementations, the method further includes: Obtain webpage privacy protection instructions input to the browser, determine the configuration webpage blur intensity of at least one accessed webpage based on the webpage privacy protection instructions, and determine the configuration webpage blur intensity as the historical webpage blur intensity.

[0008] In some possible implementations, the step of performing webpage blur update processing on the newly accessed webpage based on the blur intensity of the target webpage and displaying the newly accessed webpage after blur processing includes: Determine the page rendering tree structure corresponding to the newly created webpage, and determine a set of reference fuzzy nodes based on the page rendering tree structure; A node priority queue is determined based on the reference fuzzy node set. Based on the fuzziness intensity of the target webpage, the reference fuzzy nodes in the node priority queue are subjected to progressive fuzzy rendering processing to obtain the fuzzy new webpage content, and the fuzzy new webpage content is output and displayed.

[0009] In some possible implementations, the step of determining a node priority queue based on the reference blurred node list information, performing progressive blurred rendering on the reference blurred nodes in the node priority queue based on the blur intensity of the target webpage to obtain blurred new webpage content, and outputting and displaying the blurred new webpage content includes: Based on the reference fuzzy node list information, a node priority queue is determined, and candidate fuzzy nodes are determined based on the node priority queue. The candidate fuzzy nodes are then subjected to solid color overlay processing to obtain primary fuzzy webpage content, which is then output and displayed. The candidate blurred nodes are subjected to preliminary rendering and blurring processing to obtain intermediate blurred web page content. The primary blurred web page content is then switched to the intermediate blurred web page content for output and display. Based on the fuzziness intensity of the target webpage, the candidate fuzzy nodes are upgraded to obtain the fuzzy completed webpage content, and the intermediate fuzzy webpage content is switched to the fuzzy completed webpage for output display.

[0010] In some possible implementations, the step of upgrading the blurring of the candidate blurring nodes based on the blurring intensity of the target webpage to obtain the blurred and completed webpage content, and then switching the intermediate-level blurred webpage content to the blurred and completed webpage for output display, includes: Determine the blur pixel radius range corresponding to the blur intensity of the target webpage, and search in the memory pool for a first free blur kernel template corresponding to the blur pixel radius range; If it exists, then mark the first idle fuzzy kernel template as the target fuzzy kernel template; If it does not exist, the blurry pixel radius interval is downgraded to obtain a candidate blurry pixel radius interval, the second idle blur kernel template corresponding to the candidate blurry pixel radius interval in the memory pool is determined, and the second idle blur kernel template is updated with a pixel pattern based on the blurry pixel radius interval to obtain the target blur kernel template. Based on the target fuzzy kernel template, the candidate fuzzy nodes are subjected to Gaussian fuzzing to obtain the fuzzy completed web page content. The intermediate fuzzy web page content is then switched to the fuzzy completed web page for output and display.

[0011] Secondly, embodiments of this application provide a webpage processing apparatus, the apparatus comprising: The new webpage determination module is used to obtain the new webpage access instruction input by the browser, and determine the new webpage to be accessed based on the new webpage access instruction; The fuzz intensity correction module is used to obtain the fuzz intensity of historical web pages stored in the browser, determine the fuzz intensity correction coefficient corresponding to the newly accessed web page, and determine the fuzz intensity of the target web page corresponding to the newly accessed web page based on the fuzz intensity of the historical web pages and the fuzz intensity correction coefficient. The webpage blurring module is used to perform webpage blurring update processing on the newly accessed webpage based on the blurring intensity of the target webpage and display the newly accessed webpage after blurring.

[0012] Thirdly, embodiments of this application provide a computer storage medium having multiple instructions adapted for loading and executing the methods described above by a processor.

[0013] Fourthly, embodiments of this application provide an electronic device, which may include: a memory and a processor; wherein the memory stores a computer program adapted to be loaded by the memory and to execute the above-described method.

[0014] The beneficial effects of the technical solutions provided in this application include at least the following: The webpage processing method provided in this application obtains a new webpage access instruction input into a browser, determines a new webpage to be accessed based on the instruction, then obtains the blur intensity of historical webpages stored in the browser, determines the blur intensity correction coefficient corresponding to the new webpage to be accessed, and determines the blur intensity of the target webpage corresponding to the new webpage to be accessed based on the blur intensity of the historical webpages and the blur intensity correction coefficient. Based on the blur intensity of the target webpage, the new webpage to be accessed is then blurred and updated, and the blurred new webpage is displayed. Therefore, when a user creates a new webpage, the blur intensity correction coefficient corresponding to the new webpage to be accessed and the blur intensity of historical webpages stored in the browser can be used to efficiently and accurately create the target webpage blur intensity required for the new webpage, thereby automatically blurring the webpage according to the target webpage blur intensity, simplifying user operation and enabling rapid protection of webpage privacy content. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of a web page processing system provided in an embodiment of this application; Figure 2 This is a schematic flowchart of a webpage processing method provided in an embodiment of this application; Figure 3 This is a flowchart illustrating another webpage processing method provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a web page processing device provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of a webpage blurring module provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0017] To make the inventive objectives, features, and advantages of the embodiments of this application more apparent and understandable, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] In the description of this application, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. In the description of this application, it should be noted that, unless otherwise expressly specified and limited, "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances. Furthermore, in the description of this application, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist; for example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0019] The present application will now be described in detail with reference to specific embodiments.

[0020] like Figure 1 The image shown is a schematic diagram of a web page processing system provided in an embodiment of this application. Figure 1 As shown, a web page processing system may include at least a client cluster and a service platform 100.

[0021] In some embodiments, the client cluster may include at least one client, such as Figure 1 As shown, it specifically includes client 1 corresponding to user 1, client 2 corresponding to user 2, ..., client n corresponding to user n, where n is an integer greater than 0.

[0022] Each client in a client cluster can be an electronic device with communication capabilities, including but not limited to: wearable devices, handheld devices, personal computers, tablets, in-vehicle devices, smartphones, computing devices, or other processing devices connected to a wireless modem. Electronic devices may have different names in different networks, such as: user equipment, access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication equipment, user agent or user device, cellular phone, cordless phone, personal digital assistant (PDA), and electronic devices in 5G networks or future evolved networks.

[0023] The service platform 100 can be a standalone server device, such as a rack-mounted, blade, tower, or cabinet-type server device, or a workstation, mainframe, or other hardware device with strong computing power; or it can be a server cluster composed of multiple servers. The servers in the service cluster can be composed in a symmetrical manner, wherein each server is functionally and hierarchically equivalent in the transaction chain, and each server can provide services to the outside world independently. The independent provision of services can be understood as not requiring the assistance of other servers.

[0024] In one or more embodiments of this application, the service platform 100 can establish a communication connection with at least one client in the client cluster, and complete data interaction during the webpage processing based on the communication connection. For example, the client has a browser application installed, and the user opens a new webpage in the browser application. The client generates a new webpage access instruction for the browser input. In this scenario, the webpage processing system specifically executes the following method: obtaining the new webpage access instruction for the browser input; determining the new access webpage based on the new webpage access instruction; obtaining the blur intensity of historical webpages stored in the browser; determining the blur intensity correction coefficient corresponding to the new access webpage; determining the blur intensity of the target webpage corresponding to the new access webpage based on the blur intensity of the historical webpages and the blur intensity correction coefficient; performing webpage blur update processing on the new access webpage based on the blur intensity of the target webpage; and displaying the blurred new access webpage.

[0025] It should be noted that the service platform 100 establishes a communication connection with at least one client in the client cluster via a network for interactive communication. This network can be a wireless network or a wired network. Wireless networks include, but are not limited to, cellular networks, wireless LANs, infrared networks, or Bluetooth networks. Wired networks include, but are not limited to, Ethernet, universal serial bus (USB), or controller area networks. In one or more embodiments of the specification, technologies and / or formats including Hyper Text Markup Language (HTML), Extensible Markup Language (XML), etc., are used to represent data exchanged over the network (such as target compressed packets). Furthermore, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), and Internet Protocol Security (IPsec) can be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies can be used to replace or supplement the aforementioned data communication technologies.

[0026] The web page processing system embodiments provided in this specification and the web page processing methods shown in one or more embodiments belong to the same concept. The execution entity corresponding to the web page processing methods shown in one or more embodiments of this specification can be an electronic device, which can be the aforementioned client or the aforementioned service platform. The specific implementation process of the web page processing system embodiments can be found in the following method embodiments, and will not be repeated here.

[0027] In one embodiment, such as Figure 2 As shown, a web page processing method is proposed. This method can be implemented using a computer program and can run on a web page processing device based on the von Neumann architecture. This computer program can be integrated into applications or run as a standalone utility application.

[0028] Specifically, the methods for processing this webpage include: S201, Obtain the new webpage access instruction input by the browser, and determine the new webpage to be accessed based on the new webpage access instruction.

[0029] The "New Webpage Access" command is a command that allows a user to access a new webpage in their browser.

[0030] Specifically, the new webpage access command can be generated by the user entering a webpage address in the browser's address bar, by the user clicking a hyperlink on an already visited webpage, or by the user opening a new blank tab and then entering the webpage address. It can be understood that the new webpage access command can be generated in a scenario where a webpage already exists in the browser, or in a scenario where no webpage exists in the browser (i.e., the user opens a new browser window).

[0031] After obtaining the new webpage access instruction, the target address is parsed from the instruction to determine the new webpage indicated by the target address. Specifically, when the new webpage access instruction is triggered by the user entering a network link address in the browser address bar, the network link address entered by the user in the browser address bar can be parsed from the instruction, and this network link address is determined to be the target address. When the new webpage access instruction is triggered by the user clicking a hyperlink on an already visited webpage, the clicked hyperlink can be parsed from the instruction, and the network link address indicated by the hyperlink can be determined to be the target address. When the new webpage access instruction is triggered by the user opening a new blank tab and then entering a network link address, the network link address entered by the user in the new blank tab can be parsed from the instruction, and this network link address is determined to be the target address.

[0032] S202, obtain the blur intensity of historical web pages stored in the browser, determine the blur intensity correction coefficient corresponding to the newly accessed web page, and determine the blur intensity of the target web page corresponding to the newly accessed web page based on the blur intensity of historical web pages and the blur intensity correction coefficient.

[0033] The historical webpage blur strength refers to the most recently stored webpage blur strength in the browser. This historical webpage blur strength can be the most recently configured blur strength for a webpage that the user has opened.

[0034] The fuzz intensity correction coefficient is used to adjust the fuzz intensity of newly accessed web pages based on the fuzz intensity of historical web pages. Different newly accessed web pages can correspond to different fuzz intensity correction coefficients, and the fuzz intensity correction coefficient is strongly correlated with the newly accessed web page.

[0035] It is understood that the blur intensity of historical web pages can be any of the preset blur intensities. The preset blur intensity includes the sum of at least one fixed blur intensity configured by the browser, and the range of the preset blur intensity can be the sum of the minimum blur intensity to the fixed blur intensity, where the minimum blur intensity can be 0. In the embodiments of this application, the fixed blur intensity can be characterized by a preset blur radius. For example, the preset blur radius can be configured to be 5px, then the value of one fixed blur intensity is 5px, the value of two fixed blur intensities is 10px, and so on. The preset blur intensity can be 0px, 5px, 10px, 15px, or 20px, etc.

[0036] Specifically, after obtaining the blur intensity of historical web pages stored in the browser, it can be determined whether the blur intensity of the historical web page is the minimum blur intensity. If the blur intensity of the historical web page is not the minimum blur intensity, the blur intensity correction coefficient corresponding to the newly accessed web page is determined. Based on the blur intensity of the historical web page and the blur intensity correction coefficient, the blur intensity of the target web page corresponding to the newly accessed web page is determined.

[0037] When the blur intensity of the historical webpage is at its minimum, the process of determining the blur intensity correction coefficient for the newly accessed webpage and determining the blur intensity of the target webpage corresponding to the newly accessed webpage based on the blur intensity of the historical webpage and the blur intensity correction coefficient is cancelled, and the newly accessed webpage is then output and displayed.

[0038] Specifically, when determining the blur intensity of the target webpage, the product of the blur intensity of the historical webpage and the blur intensity correction coefficient can be determined, and this product is determined as the blur intensity of the target webpage.

[0039] In this way, when a webpage is already open in the browser and the user has already set the blur intensity for the open webpage (i.e., the browser has stored the blur intensity of historical webpages), it can not only inherit the blur state of the webpage, but also determine the blur intensity of the target webpage according to different newly accessed webpages, rather than simply copying the blur intensity set by the user. This realizes the function of intelligently blurring webpages and intelligently protecting webpage privacy.

[0040] S203, perform webpage fuzzing update processing on the newly accessed webpage based on the fuzzing intensity of the target webpage and display the newly accessed webpage after fuzzing processing.

[0041] Specifically, the browser's blur filter can be used to update the blur of a newly accessed webpage based on the blur intensity of the target webpage, and then display the blurred version. Webpage blurring can include blurring private content that needs to be blurred on the newly accessed webpage.

[0042] The webpage processing method provided in this application obtains a new webpage access instruction input into a browser, determines a new webpage to be accessed based on the instruction, then obtains the blur intensity of historical webpages stored in the browser, determines the blur intensity correction coefficient corresponding to the new webpage to be accessed, and determines the blur intensity of the target webpage corresponding to the new webpage to be accessed based on the blur intensity of the historical webpages and the blur intensity correction coefficient. Based on the blur intensity of the target webpage, the new webpage to be accessed is then blurred and updated, and the blurred new webpage is displayed. Therefore, when a user creates a new webpage, the blur intensity correction coefficient corresponding to the new webpage to be accessed and the blur intensity of historical webpages stored in the browser can be used to efficiently and accurately create the target webpage blur intensity required for the new webpage, thereby automatically blurring the webpage according to the target webpage blur intensity, simplifying user operation and enabling rapid protection of webpage privacy content.

[0043] Please see Figure 3 This is a flowchart illustrating another embodiment of a webpage processing method proposed in this application.

[0044] Specifically, the methods for processing this webpage include: S301, Obtain the new webpage access instruction input by the browser, and determine the new webpage to be accessed based on the new webpage access instruction.

[0045] For details on how step S301 is implemented, please refer to [link / reference]. Figure 2 The descriptions of the relevant steps in the illustrated embodiments will not be repeated here.

[0046] S302, obtain the blur intensity of historical web pages stored in the browser.

[0047] Specifically, one way to determine the blur strength of historical web pages is as follows: obtain the web page privacy protection instruction for browser input, determine the configuration web page blur strength of at least one accessed web page based on the web page privacy protection instruction, and determine the configuration web page blur strength as the historical web page blur strength.

[0048] It is understandable that web page privacy protection commands can be generated through the web page privacy protection actions entered by the user after opening the web page in the browser. These actions can be performed by the user configuring the web page blur intensity through the browser's privacy protection interface, or by the user configuring the blur intensity via a keyboard shortcut. Configuring the blur intensity includes at least the actions of enabling, disabling, increasing, and decreasing the blur intensity.

[0049] It's also understandable that a webpage privacy protection operation can correspond to a webpage privacy protection instruction; that is, when a webpage privacy protection operation is triggered, a webpage privacy protection instruction is generated. Different webpage privacy protection operations can generate webpage privacy protection instructions with different content, and by parsing the webpage privacy protection instruction, the webpage privacy protection operation it indicates can be determined.

[0050] Specifically, webpage privacy protection commands can include commands to enable webpage privacy protection, disable webpage privacy protection, increase webpage blur intensity, and decrease webpage blur intensity. The command to enable webpage privacy protection is generated by enabling the webpage blur function; the command to disable webpage privacy protection is generated by disabling the webpage blur function; the command to increase webpage blur intensity is generated by increasing webpage blur intensity; and the command to decrease webpage blur intensity is generated by decreasing webpage blur intensity.

[0051] After obtaining the webpage privacy protection instruction, it is determined whether a previous webpage privacy protection instruction exists. If not, the configuration webpage blur strength of at least one accessed webpage is determined based on the webpage privacy protection instruction. For example, if the current webpage privacy protection instruction is to enable webpage privacy protection, and there is no previous webpage privacy protection instruction, then the webpage blur function is enabled based on the webpage privacy protection instruction, and the configuration webpage blur strength of at least one accessed webpage is determined to be the minimum value (i.e., 0) among the preset blur strengths.

[0052] If a previous webpage privacy protection directive exists, then the configuration webpage blur strength of at least one accessed webpage is determined based on the webpage privacy protection directive and the previous configured webpage blur strength corresponding to the previous webpage privacy protection directive. For example, if the current webpage privacy protection directive is a webpage blur strength increase directive, and the previous webpage privacy protection directive is an enable webpage privacy protection directive, then a webpage blur strength increase operation is determined based on the webpage privacy protection directive, a webpage blur function enable operation is determined based on the previous webpage privacy protection directive, and a first sum value of the previous configured webpage blur strength and a fixed blur strength corresponding to the webpage blur function enable operation is determined. This first sum value is then determined as the configuration webpage blur strength.

[0053] For example, if the current webpage privacy protection instruction is a webpage blur intensity reduction instruction, and the previous webpage privacy protection instruction was a webpage blur intensity increase instruction, then the webpage blur intensity increase operation is determined based on the previous webpage privacy protection instruction, the webpage blur intensity reduction operation is determined based on the webpage privacy protection instruction, the difference between the previous configured webpage blur intensity corresponding to the webpage blur intensity increase operation and a fixed blur intensity is determined, and this difference is determined as the configured webpage blur intensity.

[0054] For example, if the current webpage privacy protection instruction is a webpage blur intensity increase instruction, and the previous webpage privacy protection instruction was also a webpage blur intensity increase instruction, then the previous webpage privacy protection instruction determines the previous webpage blur intensity increase operation. Based on the webpage privacy protection instruction, the webpage blur intensity increase operation is determined, and the second sum value of the previous configured webpage blur intensity and a fixed blur intensity corresponding to the previous webpage blur intensity increase operation is determined. The second sum value is then determined to be the configured webpage blur intensity.

[0055] S303, determine the spatiotemporal privacy score, task cluster fit score, and content sensitivity score corresponding to the newly created webpage.

[0056] Among them, the spatiotemporal privacy score is a privacy score for newly accessed web pages that is determined comprehensively based on the time dimension, geographical location dimension, and network environment dimension.

[0057] The task cluster fit score is determined based on the task cluster of the tab to which the newly visited webpage and the previously visited webpage belong.

[0058] The content sensitivity score is a sensitivity score determined based on the content of the webpage being accessed.

[0059] In one embodiment, step S303 may specifically include the following steps A1-A3: A1: Obtain the user's geographical location, obtain the network environment characteristics corresponding to the newly accessed webpage, obtain the webpage access time of the newly accessed webpage, and determine the spatiotemporal privacy score corresponding to the newly accessed webpage based on the user's geographical location, network environment characteristics, and webpage access time. A2: Obtain the tab task cluster corresponding to the previously visited webpage, and perform task relevance detection processing based on the newly visited webpage and tab task cluster to obtain the task cluster matching score corresponding to the newly visited webpage. A3: Sensitive content identification processing is performed on newly accessed web pages to obtain a content sensitivity score.

[0060] In step A1, the user's geographic location is obtained by authorizing the browser to access location information. Network environment characteristics include wireless network name identifier, network latency characteristics, and domain name resolution mode. Network latency is determined by the round-trip time from the browser to the target server. The domain name resolution mode is determined by the DNS server address and resolution path used by the browser when resolving the domain name. Webpage access time can be accurate to the minute. The URL of the newly accessed webpage, the user's geographic location, network environment characteristics, and webpage access time are input into the webpage privacy detection model. The model then performs a privacy threat assessment to obtain a spatiotemporal privacy score.

[0061] Understandably, user geolocation can be used to assess the location and context of a user's webpage visit, such as public or home environments. Public environments require privacy protection for webpages, while home environments do not. Network environment characteristics can be used to assess the network context of a user's webpage visit, such as corporate, public, or private networks. Corporate and public networks require privacy protection for webpages, while private networks do not. Webpage access time can be used to assess the time of day a user visits a webpage, such as work or rest periods. Work periods allow for privacy protection for webpages, while rest periods do not.

[0062] In step A2, the tab task clusters can include work-related task clusters, leisure and entertainment task clusters, government affairs task clusters, etc. The URL of the newly accessed webpage and the tab task cluster can be input into the webpage privacy detection model. The model then performs task relevance detection to obtain a task cluster fit score. It can be understood that if the newly accessed webpage has a high task relevance to the tab task cluster, it indicates that the newly accessed webpage can be configured with a webpage fuzziness intensity similar to the previous accessed webpage, resulting in a higher task cluster fit score. Conversely, if the newly accessed webpage has a low task relevance to the tab task cluster, it indicates that the newly accessed webpage can be configured with a webpage fuzziness intensity significantly different from the previous accessed webpage, resulting in a lower task cluster fit score.

[0063] In step A3, a webpage privacy detection model is used to identify sensitive content on the newly accessed webpage to obtain a content sensitivity score. It is understood that if a newly accessed webpage contains a significant amount of sensitive content involving personal privacy, a higher content sensitivity score will be obtained. Conversely, if a newly accessed webpage contains relatively little sensitive content involving personal privacy, a lower content sensitivity score will be obtained.

[0064] Optionally, the following example illustrates the model training process for a large-scale web privacy detection model: Model creation: Obtain a multimodal large language model, create an initial web privacy detection scenario plugin model for web privacy detection scenarios, and assemble an initial web privacy detection large model based on the multimodal large language model and the initial web privacy detection scenario plugin model; the multimodal large language model may include, but is not limited to, the DeepSeek large model, the GPT series large models, etc.

[0065] Sample data acquisition: Acquire sample data in web privacy detection scenarios. The sample data includes sample web pages, the geographical location of the sample users corresponding to the sample web pages, the characteristics of the sample network environment, the access time of the sample web pages, and the sample tab task cluster of the previous sample web page accessed by the sample web pages.

[0066] Sample data annotation: Based on the scoring requirements of web privacy detection scenarios, the sample data is annotated with spatiotemporal privacy scoring labels, task cluster fit scoring labels, and content sensitivity scoring labels.

[0067] Model training process: Input sample data into the initial web page privacy detection large model for at least one round of model training. During the forward training process: The initial web page privacy detection large model is used to determine the predicted spatiotemporal privacy score of the sample web page based on the sample user's geographical location, sample network environment characteristics, and sample web page access time. Based on the sample web page and sample tab task cluster, task correlation detection is performed to obtain the predicted task cluster fit score of the sample web page. Sensitive content identification is performed on the sample web page to obtain the predicted content sensitivity score. During the reverse training of the model, a first loss value is determined based on the predicted spatiotemporal privacy score and spatiotemporal privacy score label; a second loss value is determined based on the predicted task cluster fit score and task cluster fit score label; a third loss value is determined based on the predicted content sensitivity score and content sensitivity score label; and a model loss value is determined based on the first, second, and third loss values. The model parameters are then adjusted based on this model loss value to obtain the trained large-scale web privacy detection model.

[0068] As an illustration, the initial web page privacy detection scenario plugin model can be created based on a machine learning model.

[0069] Optionally, the training termination conditions for the large-scale web privacy detection model may include, for example, the value of the loss function being less than or equal to a preset loss function threshold, or the number of iterations reaching a preset threshold. Specific training termination conditions can be determined based on actual circumstances and are not specifically limited here.

[0070] It should be noted that the machine learning models involved in one or more embodiments of this specification include, but are not limited to, fitting of one or more of the following machine learning models: Convolutional Neural Network (CNN) model, Deep Neural Network (DNN) model, Recurrent Neural Networks (RNN) model, embedding model, Gradient Boosting Decision Tree (GBDT) model, Logistic Regression (LR) model, etc.

[0071] S304. A first correction coefficient is obtained by linear mapping based on the spatiotemporal privacy score, a second correction coefficient is obtained by linear mapping based on the task cluster fit score, and a third correction coefficient is obtained by linear mapping based on the content sensitivity score.

[0072] Specifically, a first mapping rule is determined for the spatiotemporal privacy score, a second mapping rule is determined for the task cluster fit score, and a third mapping rule is determined for the content sensitivity score. The first mapping rule is used to linearly map the spatiotemporal privacy score to obtain a first correction coefficient. The second mapping rule is used to linearly map the task cluster fit score to obtain a second correction coefficient. The third mapping rule is used to linearly map the content sensitivity score to obtain a third correction coefficient.

[0073] It is understandable that the first, second, and third mapping rules are different rules, and these rules can be configured based on expert experience.

[0074] It is also understood that the first correction coefficient belongs to the first mapping coefficient interval, the second correction coefficient belongs to the second mapping coefficient interval, and the third correction coefficient belongs to the third mapping coefficient interval. The first, second, and third mapping coefficient intervals may have overlapping numerical ranges. For example, the value range of the first mapping coefficient interval can be configured as 0.7-1.3; the value range of the second mapping coefficient interval can be configured as 0.9-1.2; and the value range of the third mapping coefficient interval can be configured as 0.75-1.25.

[0075] S305, determine the fuzziness intensity correction coefficient corresponding to the newly accessed webpage based on the first correction coefficient, the second correction coefficient and the third correction coefficient.

[0076] Specifically, the first correction coefficient, the second correction coefficient, and the third correction factor can be multiplied together to obtain the fuzz intensity correction coefficient corresponding to the newly accessed webpage.

[0077] S306, determine the fuzziness intensity of the target webpage corresponding to the newly accessed webpage based on the historical webpage fuzziness intensity and the fuzziness intensity correction coefficient.

[0078] Specifically, the product of the historical webpage blur intensity and the blur intensity correction coefficient can be determined, and this product can be used as the blur intensity of the target webpage.

[0079] S307, determine the page rendering tree structure corresponding to the newly created webpage, and determine the reference fuzzy node set based on the page rendering tree structure.

[0080] The page rendering tree structure is an ordered node tree generated based on DOM elements (i.e. nodes) and their corresponding CSS styles. In the page rendering tree structure, each node carries drawing information such as geometric dimensions, coordinates, and stacking order. This information is used to represent the appearance of the webpage and is the sole basis for any subsequent drawing, filtering, and compositing.

[0081] The reference blur node set is a collection of sensitive nodes that need to be blurred and occluded, selected from the page rendering tree structure, such as text paragraphs, images, and form fields. The reference blur node set can include the position information of each node and the pixel distance between each node and the top of the viewport.

[0082] Specifically, after obtaining the page rendering tree structure, the geometric dimensions and coordinates of each node are determined from the page rendering tree structure, thereby determining the position information of each node and the pixel distance between each node and the top of the viewport, and generating a reference blurred node set including node position information and the pixel distance between the node and the top of the viewport.

[0083] S308: Determine the node priority queue based on the reference fuzzy node list, perform progressive fuzzy rendering on the reference fuzzy nodes in the node priority queue based on the fuzziness intensity of the target webpage to obtain the fuzzy new webpage content, and output and display the fuzzy new webpage content.

[0084] The node priority queue is a dynamic queue that arranges reference blurred nodes in ascending order of their pixel distance from the top of the viewport. As the user scrolls the webpage, the node priority queue continuously displays nodes that are about to be blurred, ensuring that the area most likely to be seen by the user is processed first.

[0085] In one embodiment, performing step S308 may include the following steps B1-B3: B1: Determine the node priority queue based on the reference fuzzy node list information, determine the candidate fuzzy nodes based on the node priority queue, perform solid color overlay processing on the candidate fuzzy nodes to obtain the primary fuzzy webpage content, and output and display the primary fuzzy webpage content; B2: Perform preliminary rendering and blurring on the candidate blur nodes to obtain intermediate blur web page content, and switch the primary blur web page content to intermediate blur web page content for output display; B3: Based on the fuzziness intensity of the target webpage, upgrade the fuzziness of the candidate fuzzy nodes to obtain the fuzzy completed webpage content, and switch the intermediate fuzzy webpage content to the fuzzy completed webpage for output display.

[0086] In step B1, candidate blurred nodes are nodes that are about to become visible and require blurring, popped from the node priority queue. For example, the content displayed by a candidate blurred node on a webpage can be a piece of text or an image. The initial blurred webpage content can be understood as the blurred webpage content obtained by covering the candidate blurred nodes with a solid-color rectangular image layer to obscure their content. Specifically, firstly, a target number of candidate blurred nodes are determined from the node priority queue, and the privacy color corresponding to the candidate blurred nodes is determined, or a preset privacy color is obtained. Based on the privacy color or the preset privacy color, a solid-color rectangular image layer of the same size as the candidate blurred node is generated. The solid-color rectangular image layer is positioned at the node coordinates of the candidate blurred node, and the candidate blurred node is set to an invisible state to obtain the initial blurred webpage content, which is then output and displayed. The privacy color corresponding to the aforementioned candidate blurred node can be taken from the average color of the candidate blurred nodes.

[0087] In step B2, the intermediate-level blurred webpage content can be understood as the blurred webpage content obtained by performing low-resolution blurring processing on the candidate blurred nodes. Specifically, the candidate blurred nodes are scaled down, and the scaled-down candidate blurred nodes are blurred using the blur radius corresponding to the target blur intensity. The blurred candidate blurred nodes are then enlarged to their original size to generate an intermediate-level blurred image layer. The solid-color rectangular image layer is replaced with the intermediate-level blurred image layer to generate the intermediate-level blurred webpage content, which is then output and displayed.

[0088] In step B3, the blurred webpage content can be understood as the blurred webpage content obtained by performing full-resolution blurring processing on the candidate blurred nodes.

[0089] Specifically, step B3 may include: determining the blurred pixel radius range corresponding to the blurred intensity of the target webpage; searching in the memory pool for a first idle blurred kernel template corresponding to the blurred pixel radius range; if it exists, marking the first idle blurred kernel template as the target blurred kernel template; if it does not exist, downgrading the blurred pixel radius range to obtain candidate blurred pixel radius ranges; determining the second idle blurred kernel template corresponding to the candidate blurred pixel radius ranges in the memory pool; performing pixel pattern update processing on the second idle blurred kernel template based on the blurred pixel radius range to obtain the target blurred kernel template; performing Gaussian blur processing on the candidate blurred nodes based on the target blurred kernel template to obtain the blurred webpage content; and switching the intermediate blurred webpage content to the blurred webpage for output display.

[0090] Understandably, a preset blur pixel radius range is obtained, and the blur pixel radius range in which the blur intensity of the target webpage lies is determined from this preset range. For example, the preset blur pixel radius range includes 0-4 px, 5-8 px, 9-12 px, 13-16 px, and 17-20 px. When the blur intensity of the target webpage is 10 px, the blur pixel radius range in which the blur intensity of the target webpage lies is 9-12 px.

[0091] In this embodiment, the blur kernel template is a pre-generated two-dimensional radial gradient dot map stored in the GPU memory and used as a weight table for Gaussian blur convolution. The center of the blur kernel template has the highest brightness, and the edges gradually darken. By using the blur kernel template to perform a weighted average of pixels, a smooth blur effect is generated for the entire area at once, avoiding real-time convolution calculations and balancing performance and image quality.

[0092] Understandably, the creation and destruction of fuzzy kernel templates are expensive GPU operations. By pre-allocating a fixed number of fuzzy kernel templates in the memory pool and reusing these templates through the memory pool, fuzzy kernel template sharing can be achieved. This allows multiple fuzzy nodes to share the same fuzzy kernel template, eliminating the need to create a separate fuzzy kernel template for each node, thereby reducing GPU memory and CPU creation and destruction overhead.

[0093] Each blur kernel template in the memory pool corresponds to a specified blur pixel radius. When the blur pixel radius range of the specified blur pixel radius corresponding to a certain blur kernel template is the same as the blur pixel radius range of the target webpage blur intensity, and the blur kernel template is in an idle state, the blur kernel template is determined to be the first idle blur kernel template.

[0094] If no first free blur kernel template exists in the memory pool, the blur pixel radius interval is progressively downgraded. First, adjacent blur radius intervals smaller than the first interval are obtained. Then, a search is performed to determine if a second free blur kernel template exists for each of these adjacent intervals. If not, the downgrading process continues to obtain nearest-neighbor blur radius intervals smaller than the first intervals, and the search continues until a second free blur kernel template is found. After determining the second free blur kernel template, a target pixel pattern with a radius equal to the target webpage's blur intensity is drawn on a canvas of a preset size. This target pixel pattern is then used to overlay the original pixel pattern in the second free blur kernel template to obtain the target blur kernel template.

[0095] When performing Gaussian blurring on candidate blurred nodes based on the target blur kernel template, the candidate blurred nodes and the target blur kernel template are bound together using the browser's filter binding interface. The target blur kernel template is then used to perform Gaussian convolution on the candidate blurred nodes to obtain the blurred webpage content. The intermediate-level blurred webpage content is then switched to the blurred webpage for output display. It can be understood that after blurring a candidate blurred node, the target blur kernel template is marked as idle to allow for reuse of the blur kernel template in the memory pool.

[0096] In this way, by first applying a solid color overlay, then transitioning to low-resolution blurring, and then to full-resolution blurring to blur the nodes, the effect of instantly covering private content is achieved. Then, the private content becomes a blurry, jagged effect, and finally becomes a smooth, high-definition blur. This avoids the sharp increase in GPU compositing layer memory usage that would cause page lag due to applying CSS blurring to a large number of nodes at once, thus improving the efficiency of blurring private content on the page.

[0097] The webpage processing method provided in this application embodiment obtains a new webpage access instruction input to the browser, determines the new webpage to be accessed based on the new webpage access instruction, and then obtains the blur intensity of historical webpages stored in the browser. Subsequently, it obtains a first correction coefficient, a second correction coefficient, and a third correction coefficient through the spatiotemporal privacy score, task suitability score, and content sensitivity score of the new webpage to jointly evaluate the blur intensity correction coefficient of the new webpage from multiple dimensions, ensuring the accuracy of the blur intensity correction coefficient. Next, it determines the page rendering tree structure corresponding to the new webpage, determines a set of reference blur nodes based on the page rendering tree structure, determines a node priority queue based on the list of reference blur nodes, and performs progressive blur rendering processing on the reference blur nodes in the node priority queue based on the blur intensity of the target webpage to obtain the blurred new webpage content. Finally, it outputs and displays the blurred new webpage content. This method can save GPU compositing layer memory usage while protecting webpage privacy, ensuring device performance when maintaining webpage privacy, and avoiding the blur rendering delay caused by a sharp increase in GPU compositing layer memory usage leading to page lag due to applying CSS blur processing to a large number of nodes at once. This improves the efficiency of blur processing for page privacy content.

[0098] The following will combine Figure 4 This application provides a detailed description of the web page processing apparatus provided in its embodiments. It should be noted that... Figure 4 The web page processing apparatus shown is used to execute this application. Figures 2-3 The methods shown in the embodiments are for illustrative purposes only, illustrating the parts relevant to the embodiments of this application. For specific technical details not disclosed, please refer to this application. Figures 2-3 The example shown.

[0099] Please see Figure 4 This diagram illustrates the structure of a webpage processing apparatus according to an embodiment of this application. The webpage processing apparatus 40 can be implemented as all or part of the apparatus through software, hardware, or a combination of both. According to some embodiments, the webpage processing apparatus 40 includes a new webpage determination module 410, a fuzziness intensity correction module 420, and a webpage fuzzing processing module 430, specifically used for: The new webpage determination module 410 is used to obtain a new webpage access instruction input to the browser and determine a new webpage to be accessed based on the new webpage access instruction; The fuzz intensity correction module 420 is used to obtain the fuzz intensity of historical web pages stored in the browser, determine the fuzz intensity correction coefficient corresponding to the newly accessed web page, and determine the fuzz intensity of the target web page corresponding to the newly accessed web page based on the fuzz intensity of the historical web pages and the fuzz intensity correction coefficient. The webpage blurring module 430 is used to perform webpage blurring update processing on the newly accessed webpage based on the blurring intensity of the target webpage and display the newly accessed webpage after blurring.

[0100] Optional, the blur intensity correction module 420 includes: The first correction unit is used to determine the spatiotemporal privacy score, task cluster fit score, and content sensitivity score corresponding to the newly accessed webpage; The second correction unit is used to obtain a first correction coefficient by performing linear mapping processing based on the spatiotemporal privacy score, a second correction coefficient by performing linear mapping processing based on the task cluster fit score, and a third correction coefficient by performing linear mapping processing based on the content sensitivity score. The third correction unit is used to determine the fuzz intensity correction coefficient corresponding to the newly accessed webpage based on the first correction coefficient, the second correction coefficient, and the third correction coefficient.

[0101] Optionally, the first correction unit is specifically used for: The system obtains the user's geographic location, the network environment characteristics corresponding to the newly accessed webpage, and the webpage access time of the newly accessed webpage. Based on the user's geographic location, the network environment characteristics, and the webpage access time, it determines the spatiotemporal privacy score corresponding to the newly accessed webpage. Obtain the tab task cluster corresponding to the previously visited webpage, and perform task relevance detection processing based on the newly visited webpage and the tab task cluster to obtain the task cluster matching score corresponding to the newly visited webpage. The newly created webpage is processed to identify sensitive content, resulting in a content sensitivity score.

[0102] Optionally, the web page processing device 40 also includes: The webpage blur intensity configuration module is used to obtain webpage privacy protection instructions input by the browser, determine the configuration webpage blur intensity of at least one accessed webpage based on the webpage privacy protection instructions, and determine the configuration webpage blur intensity as the historical webpage blur intensity.

[0103] Optional, see Figure 5 The diagram shows a structural schematic of a webpage blurring module. The webpage blurring module 430 includes a first blurring unit 431 and a second blurring unit 432, specifically used for: The first fuzzy processing unit 431 is used to determine the page rendering tree structure corresponding to the newly created accessed webpage, and to determine a set of reference fuzzy nodes based on the page rendering tree structure. The second fuzzing processing unit 432 is used to determine a node priority queue based on the reference fuzzy node set, perform progressive fuzzing rendering processing on the reference fuzzy nodes in the node priority queue based on the fuzzing intensity of the target webpage to obtain the fuzzed new webpage content, and output and display the fuzzed new webpage content.

[0104] Optionally, the second blurring processing unit 432 includes: The first fuzzing processing subunit is used to determine a node priority queue based on the reference fuzzy node list information, determine candidate fuzzy nodes based on the node priority queue, perform solid color coverage processing on the candidate fuzzy nodes to obtain primary fuzzy web page content, and output and display the primary fuzzy web page content. The second fuzzing subunit is used to perform preliminary rendering fuzzing on the candidate fuzzy nodes to obtain intermediate fuzzy web page content, and to switch the primary fuzzy web page content to the intermediate fuzzy web page content for output display. The third fuzzing subunit is used to perform upgraded fuzzing processing on the candidate fuzzy nodes based on the fuzzing intensity of the target webpage to obtain the fuzzy completed webpage content, and then switch the intermediate fuzzy webpage content to the fuzzy completed webpage for output display.

[0105] Optional, the third fuzzing subunit is specifically used for: Determine the blur pixel radius range corresponding to the blur intensity of the target webpage, and search in the memory pool for a first free blur kernel template corresponding to the blur pixel radius range; If it exists, then mark the first idle fuzzy kernel template as the target fuzzy kernel template; If it does not exist, the blurry pixel radius interval is downgraded to obtain a candidate blurry pixel radius interval, the second idle blur kernel template corresponding to the candidate blurry pixel radius interval in the memory pool is determined, and the second idle blur kernel template is updated with a pixel pattern based on the blurry pixel radius interval to obtain the target blur kernel template. Based on the target fuzzy kernel template, the candidate fuzzy nodes are subjected to Gaussian fuzzing to obtain the fuzzy completed web page content. The intermediate fuzzy web page content is then switched to the fuzzy completed web page for output and display.

[0106] Please refer to Figure 6 , Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include one or more of the following components: a processor 110, a memory 120, an input device 130, an output device 140, and a bus 150. The processor 110, the memory 120, the input device 130, and the output device 140 can be connected via the bus 150.

[0107] Processor 110 may include one or more processing cores. Processor 110 connects to various parts of the electronic device using various interfaces and lines, and performs various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 120, and by calling data stored in memory 120. Optionally, processor 110 may be implemented using at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). Processor 110 may integrate one or more of a central processing unit (CPU), graphics processing unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem handles wireless communication. It is understood that the modem may also not be integrated into processor 110 and may be implemented separately using a communication chip.

[0108] The memory 120 may include random access memory (RAM) or read-only memory (ROM). Optionally, the memory 120 may include a non-transitory computer-readable storage medium. The memory 120 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (e.g., touch function, sound playback function, image playback function, etc.), instructions for implementing the various method embodiments described below, etc. The operating system may be the Android system, including systems deeply developed based on the Android system, the iOS system developed by Apple Inc., including systems deeply developed based on the iOS system, or other systems.

[0109] In order for the operating system to distinguish the specific application scenarios of third-party applications, it is necessary to establish data communication between the third-party applications and the operating system. This would allow the operating system to obtain the current scenario information of the third-party applications at any time, and then perform targeted system resource adaptation based on the current scenario.

[0110] The input device 130 is used to receive input instructions or data, and includes, but is not limited to, a keyboard, mouse, camera, microphone, or touch device. The output device 140 is used to output instructions or data, and includes, but is not limited to, a display device and a speaker. In one example, the input device 130 and the output device 140 can be combined, and the input device 130 and the output device 140 can be a touch display screen.

[0111] The touch display screen can be designed as a full-screen, curved screen, or irregularly shaped screen. It can also be designed as a combination of a full-screen and a curved screen, or a combination of an irregularly shaped screen and a curved screen; however, this application does not limit the specific design of the touch display screen.

[0112] In addition, those skilled in the art will understand that the structure of the electronic device shown in the above figures does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements. For example, the electronic device may also include radio frequency circuits, input units, sensors, audio circuits, Wireless Fidelity (WiFi) modules, power supplies, Bluetooth modules, etc., which will not be described in detail here.

[0113] In some embodiments, Figure 6 In the illustrated electronic device, the processor 110 can be used to call a web page processing method program stored in the memory 120, and specifically perform the following operations: Obtain the new webpage access instruction input into the browser, and determine the new webpage to be accessed based on the new webpage access instruction; Obtain the blur intensity of historical web pages stored in the browser, determine the blur intensity correction coefficient corresponding to the newly accessed web page, and determine the blur intensity of the target web page corresponding to the newly accessed web page based on the blur intensity of the historical web pages and the blur intensity correction coefficient. Based on the fuzziness intensity of the target webpage, the newly accessed webpage is subjected to webpage fuzziness update processing, and the newly accessed webpage after fuzziness processing is displayed.

[0114] In one embodiment, when the processor 110 determines the blur intensity correction coefficient corresponding to the newly accessed webpage, it specifically performs the following operations: Determine the spatiotemporal privacy score, task cluster fit score, and content sensitivity score corresponding to the newly created webpage; A first correction coefficient is obtained by performing linear mapping based on the spatiotemporal privacy score, a second correction coefficient is obtained by performing linear mapping based on the task cluster fit score, and a third correction coefficient is obtained by performing linear mapping based on the content sensitivity score. The fuzz intensity correction coefficient corresponding to the newly accessed webpage is determined based on the first correction coefficient, the second correction coefficient, and the third correction coefficient.

[0115] In one embodiment, when determining the spatiotemporal privacy score, task cluster fit score, and content sensitivity score corresponding to the newly accessed webpage, the processor 110 specifically performs the following operations: The system obtains the user's geographic location, the network environment characteristics corresponding to the newly accessed webpage, and the webpage access time of the newly accessed webpage. Based on the user's geographic location, the network environment characteristics, and the webpage access time, it determines the spatiotemporal privacy score corresponding to the newly accessed webpage. Obtain the tab task cluster corresponding to the previously visited webpage, and perform task relevance detection processing based on the newly visited webpage and the tab task cluster to obtain the task cluster matching score corresponding to the newly visited webpage. The newly created webpage is processed to identify sensitive content, resulting in a content sensitivity score.

[0116] In one embodiment, the processor 110 also performs the following operations: Obtain webpage privacy protection instructions input to the browser, determine the configuration webpage blur intensity of at least one accessed webpage based on the webpage privacy protection instructions, and determine the configuration webpage blur intensity as the historical webpage blur intensity.

[0117] In one embodiment, when the processor 110 performs the webpage blur update processing based on the blur intensity of the target webpage and displays the newly accessed webpage after blur processing, it specifically performs the following operations: Determine the page rendering tree structure corresponding to the newly created webpage, and determine a set of reference fuzzy nodes based on the page rendering tree structure; A node priority queue is determined based on the reference fuzzy node set. Based on the fuzziness intensity of the target webpage, the reference fuzzy nodes in the node priority queue are subjected to progressive fuzzy rendering processing to obtain the fuzzy new webpage content, and the fuzzy new webpage content is output and displayed.

[0118] In one embodiment, when the processor 110 executes the process of determining a node priority queue based on the reference blurred node list information, performing progressive blurred rendering processing on the reference blurred nodes in the node priority queue based on the blur intensity of the target webpage to obtain blurred new webpage content, and outputting and displaying the blurred new webpage content, it specifically performs the following operations: Based on the reference fuzzy node list information, a node priority queue is determined, and candidate fuzzy nodes are determined based on the node priority queue. The candidate fuzzy nodes are then subjected to solid color overlay processing to obtain primary fuzzy webpage content, which is then output and displayed. The candidate blurred nodes are subjected to preliminary rendering and blurring processing to obtain intermediate blurred web page content. The primary blurred web page content is then switched to the intermediate blurred web page content for output and display. Based on the fuzziness intensity of the target webpage, the candidate fuzzy nodes are upgraded to obtain the fuzzy completed webpage content, and the intermediate fuzzy webpage content is switched to the fuzzy completed webpage for output display.

[0119] In one embodiment, when the processor 110 performs the upgraded blurring process on the candidate blur nodes based on the blur intensity of the target webpage to obtain the blurred webpage content, and then switches the intermediate-level blurred webpage content to the blurred webpage for output display, it specifically performs the following operations: Determine the blur pixel radius range corresponding to the blur intensity of the target webpage, and search in the memory pool for a first free blur kernel template corresponding to the blur pixel radius range; If it exists, then mark the first idle fuzzy kernel template as the target fuzzy kernel template; If it does not exist, the blurry pixel radius interval is downgraded to obtain a candidate blurry pixel radius interval, the second idle blur kernel template corresponding to the candidate blurry pixel radius interval in the memory pool is determined, and the second idle blur kernel template is updated with a pixel pattern based on the blurry pixel radius interval to obtain the target blur kernel template. Based on the target fuzzy kernel template, the candidate fuzzy nodes are subjected to Gaussian fuzzing to obtain the fuzzy completed web page content. The intermediate fuzzy web page content is then switched to the fuzzy completed web page for output and display.

[0120] This application also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor to implement the web page processing method as described in the above embodiments.

[0121] This application also provides a computer program product that stores at least one instruction, which is loaded and executed by the processor to implement the web page processing method described in the above embodiments.

[0122] Those skilled in the art will recognize that the functions described in the embodiments of this application in one or more of the above examples can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of a computer program from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0123] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A webpage processing method, characterized in that, The method includes: Obtain the new webpage access instruction input into the browser, and determine the new webpage to be accessed based on the new webpage access instruction; Obtain the blur intensity of historical web pages stored in the browser, determine the blur intensity correction coefficient corresponding to the newly accessed web page, and determine the blur intensity of the target web page corresponding to the newly accessed web page based on the blur intensity of the historical web pages and the blur intensity correction coefficient. Based on the fuzziness intensity of the target webpage, the newly accessed webpage is subjected to webpage fuzziness update processing, and the newly accessed webpage after fuzziness processing is displayed.

2. The method according to claim 1, characterized in that, Determining the fuzz intensity correction coefficient corresponding to the newly accessed webpage includes: Determine the spatiotemporal privacy score, task cluster fit score, and content sensitivity score corresponding to the newly created webpage; A first correction coefficient is obtained by performing linear mapping based on the spatiotemporal privacy score, a second correction coefficient is obtained by performing linear mapping based on the task cluster fit score, and a third correction coefficient is obtained by performing linear mapping based on the content sensitivity score. The fuzz intensity correction coefficient corresponding to the newly accessed webpage is determined based on the first correction coefficient, the second correction coefficient, and the third correction coefficient.

3. The method according to claim 2, characterized in that, The determination of the spatiotemporal privacy score, task cluster fit score, and content sensitivity score corresponding to the newly accessed webpage includes: The system obtains the user's geographic location, the network environment characteristics corresponding to the newly accessed webpage, and the webpage access time of the newly accessed webpage. Based on the user's geographic location, the network environment characteristics, and the webpage access time, it determines the spatiotemporal privacy score corresponding to the newly accessed webpage. Obtain the tab task cluster corresponding to the previously visited webpage, and perform task relevance detection processing based on the newly visited webpage and the tab task cluster to obtain the task cluster matching score corresponding to the newly visited webpage. The newly created webpage is processed to identify sensitive content, resulting in a content sensitivity score.

4. The method according to claim 1, characterized in that, The method further includes: Obtain webpage privacy protection instructions input to the browser, determine the configuration webpage blur intensity of at least one accessed webpage based on the webpage privacy protection instructions, and determine the configuration webpage blur intensity as the historical webpage blur intensity.

5. The method according to claim 1, characterized in that, The step of performing webpage blur update processing on the newly accessed webpage based on the blur intensity of the target webpage and displaying the newly accessed webpage after blur processing includes: Determine the page rendering tree structure corresponding to the newly created webpage, and determine a set of reference fuzzy nodes based on the page rendering tree structure; A node priority queue is determined based on the reference fuzzy node set. Based on the fuzziness intensity of the target webpage, the reference fuzzy nodes in the node priority queue are subjected to progressive fuzzy rendering processing to obtain the fuzzy new webpage content, and the fuzzy new webpage content is output and displayed.

6. The method according to claim 5, characterized in that, The process of determining a node priority queue based on the reference blurred node list information, performing progressive blurred rendering on the reference blurred nodes in the node priority queue based on the blurred intensity of the target webpage to obtain blurred new webpage content, and outputting and displaying the blurred new webpage content includes: Based on the reference fuzzy node list information, a node priority queue is determined, and candidate fuzzy nodes are determined based on the node priority queue. The candidate fuzzy nodes are then subjected to solid color overlay processing to obtain primary fuzzy webpage content, which is then output and displayed. The candidate blurred nodes are subjected to preliminary rendering and blurring processing to obtain intermediate blurred web page content. The primary blurred web page content is then switched to the intermediate blurred web page content for output and display. Based on the fuzziness intensity of the target webpage, the candidate fuzzy nodes are upgraded to obtain the fuzzy completed webpage content, and the intermediate fuzzy webpage content is switched to the fuzzy completed webpage for output display.

7. The method according to claim 6, characterized in that, The process of upgrading the candidate blurred nodes based on the blurred intensity of the target webpage to obtain blurred and completed webpage content, and then switching the intermediate blurred webpage content to the blurred and completed webpage for output display includes: Determine the blur pixel radius range corresponding to the blur intensity of the target webpage, and search in the memory pool for a first free blur kernel template corresponding to the blur pixel radius range; If it exists, then mark the first idle fuzzy kernel template as the target fuzzy kernel template; If it does not exist, the blurry pixel radius interval is downgraded to obtain a candidate blurry pixel radius interval, the second idle blur kernel template corresponding to the candidate blurry pixel radius interval in the memory pool is determined, and the second idle blur kernel template is updated with a pixel pattern based on the blurry pixel radius interval to obtain the target blur kernel template. Based on the target fuzzy kernel template, the candidate fuzzy nodes are subjected to Gaussian fuzzing to obtain the fuzzy completed web page content. The intermediate fuzzy web page content is then switched to the fuzzy completed web page for output and display.

8. A webpage processing device, characterized in that, The device includes: The new webpage determination module is used to obtain the new webpage access instruction input by the browser, and determine the new webpage to be accessed based on the new webpage access instruction; The fuzz intensity correction module is used to obtain the fuzz intensity of historical web pages stored in the browser, determine the fuzz intensity correction coefficient corresponding to the newly accessed web page, and determine the fuzz intensity of the target web page corresponding to the newly accessed web page based on the fuzz intensity of the historical web pages and the fuzz intensity correction coefficient. The webpage blurring module is used to perform webpage blurring update processing on the newly accessed webpage based on the blurring intensity of the target webpage and display the newly accessed webpage after blurring.

9. A computer storage medium, characterized in that, The computer storage medium stores a plurality of instructions, which are adapted to be loaded by a processor and executed as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, include: A processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and executed as described in any one of claims 1 to 7.

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