Data display method, system and device for interaction security and storage medium

Abstract

The application discloses a data display method, system and device facing interactive security and a storage medium, relates to the technical field of data security, and comprises the following steps: determining an environment risk weight at the current moment based on an environment score calculator according to network parameters of a target user in a current device environment collected in real time; determining a user behavior risk weight at the current moment based on a user operation portrait according to interactive behavior data of the target user collected in real time; determining a data sensitivity weight at the current moment according to a sensitive level of data to be displayed at the current moment; determining a comprehensive weight according to the environment risk weight, the user behavior risk weight and the data sensitivity weight, and determining a fuzzy level of the data to be displayed at the current moment; and displaying the data to be displayed at the current moment according to a fuzzy strategy corresponding to the determined fuzzy level. The application dynamically adjusts the visual fuzzy level of data in combination with multi-dimensional data such as a device environment, user interactive behavior and a data sensitive level.

Description

Technical Field

[0001] This invention relates to the technical field of data security, and in particular to a data display method, system, device, and storage medium for interactive security. Background Technology

[0002] Currently, users often need to access content containing personal privacy or sensitive data when using information systems. With increasingly stringent requirements for data security and privacy protection, striking a balance between user experience and privacy protection has become a key issue in practical business operations.

[0003] Traditional data anonymization and obfuscation methods are mostly performed on the backend, providing only static processing results. This makes it difficult to adapt to changes in user behavior on the frontend in real time, leading to a disconnect between the level of obfuscation and the actual usage scenario. This not only affects user experience but may also result in the leakage of sensitive information due to insufficient obfuscation. Especially in sophisticated scenarios such as healthcare, finance, and social security, even if only some field information is exposed, combined with access patterns, location, and age information, there is still a risk that the obfuscated data can be re-identified. Therefore, we urgently need a data obfuscation display solution with dynamic adaptability. Summary of the Invention

[0004] This invention provides a data display method, system, device, and storage medium for interactive security, which solves the problems of existing static data fuzziness mechanisms, such as lack of dynamic adjustment capability, lack of user behavior perception capability, and risk of re-identification.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a data display method for interactive security, the method comprising:

[0007] Based on the network parameters of the target user in the current device environment collected in real time, the environmental risk weight at the current moment is determined based on the environmental scorer.

[0008] Based on the real-time collected interaction behavior data of the target users, the risk weight of user behavior at the current moment is determined according to the user operation profile;

[0009] Determine the data sensitivity weight at the current moment based on the sensitivity level of the data to be displayed at the current moment;

[0010] A comprehensive weight is determined based on the environmental risk weight, the user behavior risk weight, and the data sensitivity weight, and the fuzziness level of the data to be displayed at the current moment is determined based on the magnitude of the comprehensive weight; the magnitude of the comprehensive weight is positively correlated with the fuzziness level of the data to be displayed.

[0011] The data to be displayed at the current moment is displayed according to the fuzziness strategy corresponding to the determined fuzziness level; the magnitude of the fuzziness level is positively correlated with the preset fuzziness degree of data display in the fuzziness strategy.

[0012] In one possible implementation, for each blur level, when setting the blur level of data display, different preset processing methods are used for different types of sensitive data in the data to be displayed; the preset processing methods include data generalization processing, data segmentation masking processing, text replacement, and layer filters.

[0013] In one possible implementation, before displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the method further includes:

[0014] Obtain the user-defined fuzziness level for sensitive data in the data to be displayed at the current moment;

[0015] The fuzzy level determined based on the comprehensive weight is compared with the custom fuzzy level, and the fuzzy level with the larger fuzzy level is taken as the final fuzzy level.

[0016] In one possible implementation, when displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the method further includes:

[0017] Real-time reading of the blurring strategy corresponding to the current rendering data;

[0018] Determine whether the blurring strategy corresponding to the current rendered data meets the requirements of the blurring strategy corresponding to the determined blur level, and obtain the determination result;

[0019] If the judgment result is negative, the current rendering data will be forcibly switched to the blur strategy corresponding to the maximum blur level for display.

[0020] In one possible implementation, the method further includes: when a forced switch is performed, using a gradient animation or a mask layer to gradually increase the display blur of the currently rendered data.

[0021] In one possible implementation, after displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the method further includes:

[0022] Monitor the interactive behavior data of the target user collected in real time;

[0023] When the target user is detected to be offline, the blur level of the currently displayed data is increased, and the blur level of the currently displayed data is updated according to the blur strategy corresponding to the increased blur level. The offline state includes window out of focus, tab switching, and no user interaction within a preset time interval.

[0024] In one possible implementation, when updating the data display state according to the fuzzy strategy corresponding to the improved fuzziness level, the method specifically includes:

[0025] Based on the blurring strategy corresponding to the improved blur level, the blur level of the currently displayed data is gradually increased using CSS layer animation or canvas layer animation.

[0026] Secondly, the present invention provides a data display system for interactive security, the system comprising:

[0027] The environmental risk assessment module is used to determine the environmental risk weight at the current moment based on the network parameters of the target user in the current device environment collected in real time and the environmental scorer.

[0028] The user behavior risk assessment module is used to determine the user behavior risk weight at the current moment based on the user operation profile and the real-time collected interaction behavior data of the target user.

[0029] The data evaluation module is used to determine the data sensitivity weight at the current moment based on the sensitivity level of the data to be displayed at the current moment;

[0030] The comprehensive weight determination module is used to determine a comprehensive weight based on the environmental risk weight, the user behavior risk weight, and the data sensitivity weight, and to determine the fuzziness level of the data to be displayed at the current time based on the magnitude of the comprehensive weight; the magnitude of the comprehensive weight is positively correlated with the fuzziness level of the data to be displayed.

[0031] The data display module is used to display the data to be displayed at the current time according to the fuzziness strategy corresponding to the determined fuzziness level; the magnitude of the fuzziness level is positively correlated with the preset data display fuzziness degree in the fuzziness strategy.

[0032] In one possible implementation, in the data display module, the blurring strategy corresponding to each blur level is configured as follows: when setting the blur level of data display, different preset processing methods are adopted for different types of sensitive data in the data to be displayed; the preset processing methods include data generalization processing, data segmentation masking processing, text replacement, and layer filters.

[0033] In one possible implementation, before displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the data display module is further configured to execute:

[0034] Obtain the user-defined fuzziness level for sensitive data in the data to be displayed at the current moment;

[0035] The fuzzy level determined based on the comprehensive weight is compared with the custom fuzzy level, and the fuzzy level with the larger fuzzy level is taken as the final fuzzy level.

[0036] In one possible implementation, when displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the data display module is specifically configured to execute:

[0037] Real-time reading of the blurring strategy corresponding to the current rendering data;

[0038] Determine whether the blurring strategy corresponding to the current rendered data meets the requirements of the blurring strategy corresponding to the determined blur level, and obtain the determination result;

[0039] If the judgment result is negative, the current rendering data will be forcibly switched to the blur strategy corresponding to the maximum blur level for display.

[0040] In one possible implementation, the data display module is configured to execute the following during a forced switch:

[0041] Use gradient animations or masking layers to gradually increase the blur level of the currently rendered data.

[0042] In one possible implementation, the data display system further includes an exit lock processing module. After displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the exit lock processing module is configured to execute:

[0043] Monitor the interactive behavior data of the target user collected in real time;

[0044] When the target user is detected to be offline, the blur level of the currently displayed data is increased, and the blur level of the currently displayed data is updated according to the blur strategy corresponding to the increased blur level. The offline state includes window out of focus, tab switching, and no user interaction within a preset time interval.

[0045] In one possible implementation, when updating the data display state according to the fuzzy strategy corresponding to the increased fuzziness level, the departure locking processing module is specifically configured to execute:

[0046] Based on the blurring strategy corresponding to the improved blur level, the blur level of the currently displayed data is gradually increased using CSS layer animation or canvas layer animation.

[0047] Thirdly, the present invention provides an electronic device comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set, or an instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the data display method for interactive security described above.

[0048] Fourthly, the present invention provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the data display method for interactive security described above.

[0049] The data display method for interactive security provided in this invention, in practical applications, first determines the environmental risk weight at the current moment based on the network parameters of the target user in the current device environment collected in real time; then determines the user behavior risk weight at the current moment based on the interactive behavior data of the target user collected in real time; and finally determines the data sensitivity weight at the current moment based on the sensitivity level of the data to be displayed. Next, a comprehensive weight is determined based on the determined environmental risk weight, user behavior risk weight, and data sensitivity weight at the current moment, and the fuzziness level of the data to be displayed at the current moment is determined based on the comprehensive weight. Finally, the data to be displayed is performed with a preset level of data fuzziness according to the fuzziness strategy corresponding to the fuzziness level. This invention can dynamically adjust the visualization fuzziness level of data during user interaction with the page by combining multi-dimensional data such as device environment, user interaction behavior, and data sensitivity level, thereby solving the problems of existing static data fuzziness mechanisms, such as lack of dynamic adjustment capability, lack of user behavior perception capability, and the risk of re-identification. Attached Figure Description

[0050] Figure 1 A flowchart illustrating the steps of a data display method for interactive security provided in this embodiment of the invention;

[0051] Figure 2 This is a structural block diagram of a data display system for interactive security provided in an embodiment of the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of this disclosure, unless otherwise stated, "a plurality of" means two or more. Furthermore, the use of "based on" or "according to" implies openness and inclusiveness, because processes, steps, calculations, or other actions "based on" or "according to" one or more of the stated conditions or values ​​may in practice be based on additional conditions or beyond the stated values.

[0054] Currently, traditional data anonymization and obfuscation methods suffer from problems such as being vague and static, lacking dynamic adjustment capabilities, lacking behavior perception mechanisms, being disconnected from system context, and being difficult to prevent re-identification attacks.

[0055] Among them, the fuzzy static nature and lack of dynamic adjustment capability refer to the fact that most existing methods of displaying fuzzy data are based on the desensitization rules set in the backend, and the degree of fuzziness of the displayed content is fixed, making it impossible to adjust the degree of fuzziness of the data display in real time according to user interaction behavior.

[0056] The lack of a behavior perception mechanism means that existing technologies cannot monitor user interaction behavior data in real time, thereby dynamically adjusting the fuzziness level of the data based on the user's level of attention to certain data.

[0057] Decoupling from the system context refers to the inability of existing technologies to dynamically adjust fuzzy strategies based on network parameters in the current device environment.

[0058] The difficulty in preventing re-identification attacks refers to the fact that even after data anonymization, existing technologies can still accurately infer combinations of sensitive fields. Existing technologies cannot respond dynamically and increase the level of fuzziness to block the data re-identification path.

[0059] To address the problems of existing static data fuzziness mechanisms, such as lack of dynamic adjustment capabilities, lack of user behavior perception capabilities, and the risk of re-identification, this invention provides a data display method, system, device, and storage medium for interactive security.

[0060] like Figure 1As shown, in a first aspect, embodiments of the present invention provide a data display method for interactive security, the method comprising:

[0061] Step 101: Based on the network parameters of the target user in the current device environment collected in real time, determine the environmental risk weight at the current moment based on the environmental scorer.

[0062] Specifically, the network parameters collected in real time for the target user in the current device environment include, but are not limited to, the `navigator.connection.effectiveType` parameter for identifying whether the current device is connected to a 2G, 4G, or WiFi network; the `User-Agent` parameter for identifying whether the target user is using a regular browser; the `Data Saver` parameter for identifying whether the target user has enabled data saving mode; the IP address location; browser fingerprinting or behavioral characteristics to determine whether the user is using a proxy or VPN; and login parameters for sensitive channels such as remote desktop login, cloud desktop, and RDP environment (remote desktop environment). The collection of these parameters is for further assessment of the environmental risk weight of the current device environment. In this embodiment, the real-time collection of network parameters is specifically implemented through an environmental detector.

[0063] Next, an environment scorer scores the real-time collected network parameters to obtain the environmental risk weight for the current moment. The environment scorer has predefined scoring rules for environmental parameters. After receiving the real-time collected network parameters, the environment scorer determines the environmental risk weight based on these predefined rules. For example, if the network parameters indicate that the target user is accessing data from the company's intranet through a trusted browser, and the network latency is below a preset value, with no proxy or VPN, the environment scorer outputs a low environmental risk weight, approximately 0.1, indicating a low-risk environment. Conversely, if the system detects that the user is accessing data from an overseas proxy, or that a virtual desktop environment exists with an unstable network connection, the environment scorer outputs a high environmental risk weight, approximately 0.8 or even higher, indicating a high-risk environment.

[0064] In this embodiment of the invention, the environment scorer has predefined scoring rules for environmental parameters that support configurable adjustments. That is, users can adjust the trusted network boundaries of each network parameter and their corresponding scoring values ​​according to the actual business needs of accessing data.

[0065] In this embodiment of the invention, the environment scorer primarily assesses the data risks posed by various network parameters collected in real time by the target user. For example, when the current device environment is detected:

[0066] Enabling Data Saver mode will increase the environmental risk weight score by 0.2.

[0067] If the environment is in a remote desktop (RDP) or cloud desktop environment, the environmental risk weight score will be increased by 0.5.

[0068] If the browser used has incognito mode or a script blocker plugin enabled, the environmental risk weight score will be increased by 0.3.

[0069] If the IP address used comes from a proxy / Tor / cloud host, the environmental risk weight score will be increased by 0.4.

[0070] If the screen resolution of the device being used is within the preset resolution range, the environmental risk weight score will be increased by 0.2.

[0071] The environmental scorer sums the scores of each item according to the above evaluation rules and outputs the total environmental risk weight corresponding to the current equipment environment.

[0072] In addition, the environmental scorer can preset risk assessment thresholds. Based on the output environmental risk weights and the preset risk assessment thresholds, the risk status of the current equipment environment is determined. This risk status includes high risk and low risk, and an equipment environment warning is issued when the risk status is high.

[0073] Step 102: Based on the real-time collected interaction behavior data of the target users, determine the user behavior risk weight at the current moment based on the user operation profile.

[0074] Specifically, a series of user interaction events on the data access page are collected in real time, including mouse hover events (hoverTime), click count (clickCount), page switching frequency, whether the user is a first-time visitor, and interaction paths within the page, to obtain the user's interaction behavior data. In this embodiment, the collection of interaction behavior data is achieved by binding standard DOM events; these DOM events include mouseenter, mouseleave, click, and visibilitychange events.

[0075] The real-time interactive behavior data of the target user is input into the user operation profile built from the historical interactive behavior data. The user operation profile is used to analyze the interactive behavior of the target user at the current moment, thereby inferring the credibility or data usage intention of the target user at the current moment. The interactive behavior data of the target user at the current moment is scored to obtain the user behavior risk weight of the target user at the current moment.

[0076] In this embodiment, the user operation profile analysis yielded the following:

[0077] If the time spent on the data access page is less than 0.2 seconds, or if the data access page is frequently refreshed, the score of the user behavior risk weight will be increased by 0.3.

[0078] If the mouse movement trajectory is abnormal, such as the mouse moving straight or mechanically, the score of the user behavior risk weight will be increased by 0.3.

[0079] If the data access page is scrolled but not clicked, the user behavior risk score will be increased by 0.2.

[0080] If a user frequently accesses sensitive fields such as ID card number and salary information, the user's behavior risk score will be increased by 0.4.

[0081] Frequent switching of browser tabs or loss of focus will increase the user behavior risk score by 0.2.

[0082] Based on the above-mentioned preset evaluation rules, the scores of each item are added together to output the total user behavior risk weight corresponding to the current device environment. When displaying data in a fuzzy manner, the more abnormal the behavior, the higher the degree of data fuzziness should be defined.

[0083] In practical applications, the scoring rules and scores set based on user operation profiles can be customized according to actual business needs.

[0084] Step 103: Determine the data sensitivity weight at the current moment based on the sensitivity level of the data to be displayed at the current moment.

[0085] Specifically, since different types of data in the data to be displayed have different levels of sensitivity, this invention first classifies the data to be displayed into different sensitivity levels according to the sensitivity of different types of data, and different sensitivity levels correspond to different predefined weight values.

[0086] In this embodiment, the sensitivity level of mobile phone number, ID card, and bank card number is S, with a corresponding data sensitivity weight of +0.5; the sensitivity level of health information, disease, and historical medical records is A, with a corresponding data sensitivity weight of +0.4; the sensitivity level of address information, consumption records, and visitor records is B, with a corresponding data sensitivity weight of +0.3; and the sensitivity level of age, gender, and occupation is C, with a corresponding data sensitivity weight of +0.2.

[0087] Therefore, in step 103, the data sensitivity weight corresponding to each data type can be obtained based on its sensitivity level. Furthermore, the sensitivity levels of different data types and their corresponding data sensitivity weights can be adjusted according to the actual application scenario.

[0088] In this embodiment of the invention, steps 101, 102 and 103 are executed synchronously to obtain the environmental risk weight, user behavior risk weight and data sensitivity weight at the current moment.

[0089] Step 104: Determine the comprehensive weight based on the environmental risk weight, user behavior risk weight, and data sensitivity weight, and determine the fuzziness level of the data to be displayed at the current moment based on the magnitude of the comprehensive weight.

[0090] Among them, the magnitude of the comprehensive weight is positively correlated with the fuzziness level of the data to be displayed.

[0091] Specifically, the environmental risk weight, user behavior risk weight, and data sensitivity weight determined in steps 101-103 are added together to obtain a comprehensive weight. The fuzziness level of the data to be displayed at the current moment is determined based on the comprehensive weight and a preset threshold; the higher the comprehensive weight, the higher the fuzziness level of the data to be displayed.

[0092] In this embodiment of the invention, the fuzziness level can be set to three levels: high fuzziness, medium fuzziness, and low fuzziness. The preset thresholds include a first preset threshold and a second preset threshold, with the first preset threshold being greater than the second preset threshold. For example, the first preset threshold is 1.0, and the second preset threshold is 0.6. When the overall weight is greater than or equal to 1.0, the fuzziness level of the data to be displayed at the current moment is high fuzziness; when the overall weight is greater than or equal to 0.6 and less than 1.0, the fuzziness level of the data to be displayed at the current moment is medium fuzziness; and when the overall weight is less than 0.6, the fuzziness level of the data to be displayed at the current moment is low fuzziness.

[0093] Step 105: Display the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level.

[0094] Among them, the magnitude of the fuzziness level is positively correlated with the preset fuzziness level of the data display in the fuzziness strategy.

[0095] The degree of fuzziness in data display refers to the extent to which precise values ​​in data are converted into fuzzy values. The higher the fuzziness level, the greater the degree of fuzziness in the data display.

[0096] Specifically, the fuzzy strategy corresponding to the low fuzziness level will fully display all precise data information; the fuzzy strategy corresponding to the medium fuzziness level will display data with a sensitivity level of C in plaintext, and perform data generalization processing on data with a sensitivity level of B and above; the fuzzy strategy corresponding to the high fuzziness level will perform data generalization processing on data with a sensitivity level of C and above, and the degree of data generalization processing for the high fuzziness level is greater than that for the medium fuzziness level.

[0097] In this embodiment, the low fuzziness level displays all accurate information; the medium fuzziness level displays the age as "33 years old", the address as "a certain city", and the amount as an integer; the high fuzziness level displays the age as "30-40 years old", the address as "a certain province", and the amount as "10,000~20,000".

[0098] In practical applications, the data display method for interactive security provided in this invention first determines the environmental risk weight at the current moment based on the network parameters of the target user in the current device environment collected in real time, determines the user behavior risk weight at the current moment based on the interactive behavior data of the target user collected in real time, and determines the data sensitivity weight at the current moment based on the sensitivity level of the data to be displayed at the current moment. Then, a comprehensive weight is determined at the current moment based on the determined environmental risk weight, user behavior risk weight, and data sensitivity weight, and the fuzziness level of the data to be displayed at the current moment is determined based on the comprehensive weight. Finally, the data to be displayed is performed with a preset fuzziness level according to the fuzziness strategy corresponding to the fuzziness level.

[0099] This invention can dynamically adjust the visualization fuzziness level of data by combining multi-dimensional data such as device environment, user interaction behavior, and data sensitivity level during user interaction with the page, thereby solving the problems of existing static data fuzziness mechanisms, such as lack of dynamic adjustment capability, lack of user behavior perception capability, and risk of re-identification.

[0100] Furthermore, for each level of fuzziness, different preset processing methods are used for different types of sensitive data in the data to be displayed when setting the degree of fuzziness in the data display.

[0101] The preset processing methods include data generalization, data segmentation masking, text replacement, and layer filters.

[0102] Compared to traditional fuzzy strategies that rely solely on character replacement (e.g., ***) for coarse-grained encoding, this invention provides diverse fuzzy strategies for different types of sensitive fields. For example, when displaying age, the actual age "43" is generalized to "40~45", "40+", and "middle-aged" based on the overall weight. When displaying regional information, a geospatial hierarchical fuzzy strategy is adopted. At low fuzziness levels, the actual address is displayed normally; at medium fuzziness levels, the address is generalized to "Haidian District, Beijing"; and at high fuzziness levels, the address is generalized to "Beijing" or "North China," achieving data minimization and compatibility with various usage scenarios.

[0103] When displaying the bank card number field, a rendering strategy is employed. Based on the overall weight of the blur level, segmented blurring is applied using data segmentation masking, text replacement, and layer filters. For example, the bank card number field "6222 8888 1234 5678" is displayed in full plaintext at a low blur level; at a medium blur level, the field is partially blurred, specifically as "6222 8888 1234 ****" or "6222 **** ****5678"; and at a high blur level, the entire field is blurred, specifically as "**** **** **** ****".

[0104] Furthermore, before displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the method also includes:

[0105] Get the user's custom fuzziness level for sensitive data in the data to be displayed at the current moment.

[0106] The fuzzy level determined by the comprehensive weight is compared with the user-defined fuzzy level, and the larger fuzzy level is taken as the final fuzzy level.

[0107] In other words, based on dynamic weight judgment, this invention further introduces a mandatory security strategy to limit the minimum threshold for fuzzy data display, ensuring that even if a user view "boosts credibility," it cannot completely bypass the fuzzy limitation of this invention, thereby achieving minimum access control over sensitive data.

[0108] Specifically, for each type of sensitive data in the data to be displayed, such as ID card numbers, bank card information, addresses, and mobile phone numbers, a separate set of independent fuzzy constraint rules can be set. These rules define the fuzziness levels for different types of sensitive data. When displaying the data, the fuzziness level with the larger fuzziness level (determined based on comprehensive weights and the user-defined fuzziness level) is used as the final fuzziness level for that sensitive data.

[0109] In this embodiment, the mandatory security policy settings for sensitive data in the data to be displayed include, but are not limited to, minimum fuzzy weight settings, intranet access settings, prohibition of full plaintext display settings, and mouse hover time limit settings.

[0110] The minimum fuzz weight setting refers to customizing the minimum fuzz level for a specific sensitive data. For example, if the custom minimum fuzz level for a sensitive data is 0.7, even if the calculated overall weight is only 0.3, the fuzz level corresponding to 0.7 will be used as the final fuzz level, and the sensitive data can only be displayed in a partially or fully fuzzy state.

[0111] Internal network access settings refer to restricting the display of certain sensitive data to only within the internal network or a whitelist of IP addresses. If the current network environment is detected as a public network, VPN, or cloud host environment, the sensitive value will be forcibly obscured.

[0112] The setting to prohibit full plaintext display means that certain sensitive data cannot be fully displayed even in a trusted environment. Instead, it can only be displayed in a forced obfuscated form, such as plaintext at the end, obfuscated prefix, or range value. Examples include ID card numbers and bank card numbers, which are data with the risk of being re-identified.

[0113] The mouse hover time limit setting specifically refers to setting a maximum hover threshold to prevent users from hovering for too long or for OCR tools to recognize data field information. If the time limit is exceeded, a field re-blurring mechanism will be triggered, and an alarm message will be displayed.

[0114] Furthermore, when displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the method also includes:

[0115] Read the blurring strategy corresponding to the current rendering data in real time.

[0116] Determine whether the blurring strategy corresponding to the current rendered data meets the requirements of the blurring strategy corresponding to the determined blur level, and obtain the judgment result.

[0117] If the result is negative, the current rendering data will be forcibly switched to the blur strategy corresponding to the maximum blur level for display.

[0118] In this embodiment, the front-end component reads the blurring strategy corresponding to the data in real time when rendering the current data, and determines whether the blurring strategy corresponding to the currently rendered data meets the requirements of the blurring strategy corresponding to the determined blur level. If the requirements are not met, the current rendered data is forcibly switched to the blurring strategy corresponding to the maximum blur level for display, and the access behavior and trigger time are recorded in the console log for subsequent security audit work.

[0119] Furthermore, when performing a forced switch, a gradient animation or mask layer is used to gradually increase the blur level of the currently rendered data.

[0120] In other words, this embodiment has a strategy-level animation response mechanism. When a forced switch occurs, it uses gradient animation or mask layer visual feedback to avoid instantaneous information jumps, thereby improving the naturalness of the user experience. At the same time, it uses blur animation to distinguish the behavioral differences between "system active strategy response" and "normal blur gradual appearance", further enhancing traceability.

[0121] When the system detects high-risk environments such as public Wi-Fi or remote desktops, it can forcibly switch the fuzzy strategy corresponding to the maximum fuzziness level for display, preventing users from accidentally operating or tampering with the client state, thereby improving the system's anti-recognition capability and robustness.

[0122] Furthermore, after displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the method also includes:

[0123] Monitor the interactive behavior data of target users collected in real time.

[0124] When the target user is detected to be offline, the blur level of the currently displayed data is increased, and the blur level of the currently displayed data is updated according to the blur strategy corresponding to the increased blur level.

[0125] The offline state includes window out of focus, tab switching, and no user interaction within a preset time interval.

[0126] Furthermore, when updating the data display status according to the fuzzy strategy corresponding to the improved fuzziness level, the specific method is as follows:

[0127] Based on the blurring strategy corresponding to the improved blur level, the blur level of the currently displayed data is gradually increased using CSS layer animation or canvas layer animation.

[0128] In other words, during actual data access, short-term user interruptions, such as switching browser tabs, minimizing windows, or leaving the keyboard, can expose sensitive data to others, creating a risk of data leakage. Therefore, this invention incorporates a "reverse blur animation mechanism" as the final step in a dynamic data blur display scheme. When the system detects that the user has left the operating environment (i.e., is offline), it automatically restores all plaintext and low-blurry data to a higher blur level, providing a visual transition to ensure that the data defaults to a safe, high-blurry level when there is no user interaction.

[0129] In this embodiment of the invention, the rollback fuzzy animation mechanism is implemented based on an animation triggering system that combines real-time monitoring of interactive behavior data with data fuzziness level control.

[0130] Specifically, the system monitors real-time interaction data for events such as window defocusing, tab switching, and no user interaction within a preset time interval to determine if the user has entered an offline state. If the user has entered an offline state, the system triggers a fuzzy rollback logic.

[0131] To avoid the impact on user experience caused by sudden data changes, CSS or canvas layer animations are used to gradually transition the displayed data from plaintext or semi-plaintext to a completely blurred state. This visual gradient effect not only aligns with current UI design trends but also provides users with a clear "safe state transition" prompt.

[0132] Furthermore, after the blur animation is executed, the data whose blur level has been adjusted will not immediately revert to plain text display. The original blur level will only be restored when the user re-enters the interactive state, for example, by moving the cursor over the data or actively clicking to view it. This design aims to prevent accidental reverts from directly exposing sensitive data. This invention also supports setting an "unlock cooldown period" for data, meaning that the original text cannot be directly viewed for a period of time after the blur reverts.

[0133] Furthermore, each sensitive data field maintains an independent animation state controller at the component level, supporting the triggering and termination of animation intensity for the field. This design facilitates the later expansion of fuzzy logic for specific fields, such as using fuzzy masking for identity information and dynamic numeric fuzzing for monetary fields.

[0134] The data display method for interactive security of the present invention can dynamically adjust the fuzzy strategy and customize the switching of the display security level according to the network parameters, interactive behavior data and the sensitivity level of the data to be displayed at the current device environment. While improving the security of data display, it ensures the controllability and smoothness of user interaction experience.

[0135] When determining the risk weight of user behavior, this invention can perceive behavioral characteristics such as the dwell time, frequency of operation, and click trajectory of user operations, and combine them with the network environment status (e.g., whether it is in an RDP remote environment, data saving mode, network fluctuation environment, etc.) to accurately assess the risk level of data display.

[0136] This invention uses three dimensions of current-time data—environmental risk weight, user behavior risk weight, and the sensitivity level of the data to be displayed—to determine a comprehensive weight, thereby determining the fuzziness level corresponding to the current-time data. This enables dynamic allocation of fuzziness levels and automatic upgrading or downgrading of fuzzy measurements, thereby improving the self-adjustment and self-recovery capabilities of the solution and reducing manual intervention.

[0137] This invention determines the fuzziness level of the data to be displayed by inheriting the comprehensive weight through the backend interface, and feeds back the corresponding fuzziness strategy; after receiving the above instructions sent by the backend component, the frontend component automatically renders the corresponding fuzziness strategy, truly realizing "unified cloud management and real-time frontend response" of fuzziness strategy.

[0138] The forced execution mechanism set up in this invention can force the display mode corresponding to the highest fuzziness level to be enabled in high-risk environments, preventing users from accidentally operating or tampering with the client state, thereby improving the system's anti-recognition capability and robustness.

[0139] The automatic offline blur rollback mechanism set up in this invention can immediately cover sensitive information based on blur rollback animation when the user is offline, effectively preventing information leakage or bystander attacks and ensuring the "lock-in-out" security of content.

[0140] In this embodiment of the invention, the technical architecture of the data display scheme for interactive security includes a perception layer, a decision layer, and a display layer. The collection of network parameters under the current device environment and the collection of user interaction behavior data are both implemented in the perception layer. The core objective of this layer is to provide reliable environmental and behavioral data, providing a basis for the fuzzification strategy decisions of the upper layers, and ensuring that the dynamic fuzziness scheme of this invention achieves an intelligent balance between security and usability.

[0141] The network parameters under the current device environment are collected through a network environment identification module. This module monitors the network environment accessed by the client in real time to identify potential risk factors. Specifically, the module mainly collects information including the client's public IP address, the IP address's local area, whether the connection is through a proxy or VPN, whether it originates from the company's intranet, and the primary network type (such as cellular mobile network or home broadband). A front-end JavaScript script is used to initially determine the network type (e.g., detecting leaked LAN addresses and User-Agent information via WebRTC), and further queries the IP address's location, carrier information, and whether it matches the IP blacklist of VPNs or anonymous proxies by calling the back-end interface. In other words, this invention effectively identifies, at the perception layer, malicious overseas crawlers, users using VPNs to spoof their location, or temporary external device access behaviors that pose a data leakage risk through the network environment identification module, thus providing a basis for subsequent data ambiguity assessment.

[0142] User interaction data is collected through a user behavior monitoring module that continuously tracks user interactions on the page to assess the authenticity and risk of visits. Specifically, this module listens for a series of user actions on the page, including mouse hover events (hoverTime), click counts (clickCount), page switching frequency, whether the user is a first-time visitor, and in-page interaction paths. This behavioral data collection is primarily achieved by binding to standard DOM events such as mouseenter, mouseleave, click, and visibilitychange. By collecting this data, a user profile is built to determine whether the visitor is a genuine user with normal usage intent or a script program simulating behavior using automated tools. In certain high-security scenarios, this module can also be combined with behavior recognition models (such as swipe trajectory stability assessment) to further enhance the accuracy of user credibility determination.

[0143] In summary, the perception layer serves as the infrastructure for underlying data acquisition. By real-time sensing and quantification of data from both the network environment and user behavior dimensions, it provides crucial input for the upper-layer dynamic fuzzy weight calculation and strategy execution, enabling the entire fuzzy processing mechanism to intelligently adjust itself "according to the user, time, and environment." This perception-driven front-end fuzzy display method significantly enhances the adaptability and security of the processing architecture, and is one of the fundamental supports for the technological innovation of this invention.

[0144] The decision-making layer, situated above the perception layer, primarily handles intelligent decision-making regarding the degree of fuzziness in data display. The core design of this layer combines multi-dimensional perception data, including user behavior and access environment, with weighted calculations and a strategy engine to dynamically adjust the clarity of sensitive information displayed on the front end. This ensures user usability while minimizing the risk of data leakage. Specifically, it dynamically adjusts the fuzziness of data display based on a comprehensive weight determined by real-time collected network parameters, interaction behavior data, and the sensitivity level of the displayed data. For example, when the system detects that a user's current network environment is not an intranet and exhibits proxy access characteristics, even if their behavior trajectory indicates a normal user, the corresponding comprehensive weight will control the final data display to be highly fuzzy, displaying sensitive information. Conversely, in a trusted network environment, such as when a user is accessing from an enterprise intranet and exhibits continuous, stable, and trustworthy interaction behavior, the fuzziness of the data display will gradually decrease, allowing sensitive information to be used normally.

[0145] In addition to comprehensive weight calculation, the decision-making level also has a policy enforcement mechanism, which sets a user-defined sensitivity level for a certain sensitive data. Before rendering, the front-end component compares the current state with the policy. When the sensitivity level corresponding to the comprehensive weight is lower than the user-defined sensitivity level, forced blurring display is automatically enabled to avoid data leakage due to misjudgment.

[0146] Therefore, the decision-making level not only achieves "intelligent control" at the front end, but also forms a closed-loop management and control system from data perception to strategy implementation through the precise inheritance of organizational strategies. It has high practicality and engineering implementation value, and is one of the key technological innovations of this invention.

[0147] The presentation layer plays a crucial role in visualizing the results of "security awareness + risk decision-making." Its core design goes beyond traditional "masking"; it employs a multi-layered, semantically aware, and progressively blurring display scheme for various types of sensitive data, based on defined comprehensive weights. The presentation layer enables users to see dynamic and controllable blurred visual feedback in different access contexts, thus balancing the practical needs of data usage efficiency and privacy protection.

[0148] When rendering graphics, the presentation layer combines CSS masking and Canvas filter technology, and supports a high-security rendering mode to prevent screenshot recognition and OCR attacks. Furthermore, to enhance the dynamic nature of protection, the presentation layer integrates an animation fallback mechanism; when the user's mouse leaves a sensitive area, the page switches, or the operation times out, the system will automatically trigger the onBlur animation, restoring the maximum blur frame by frame to prevent information leakage caused by subsequent screen sharing, page screenshots, or front-end remnants.

[0149] Therefore, the presentation layer not only embodies the finely adjustable fuzzy granularity, but also constructs a more humanized and intelligent visual privacy protection component through semantic understanding and data type adaptation. It is suitable for practical deployment in multiple scenarios such as medical care, finance, and e-commerce, and has significant technical promotion value and innovation.

[0150] In the data visualization solution architecture for interactive security, the perception layer is responsible for providing real-time data; the decision layer calls upon the data from the perception layer and outputs a comprehensive weight based on preset strategies; the visualization layer uses the comprehensive weight to determine the degree of ambiguity in the data display and provides complex animation feedback. The entire technical architecture achieves closed-loop control from "environment + behavior perception --> decision scoring --> visualization output".

[0151] like Figure 2 As shown, in a second aspect, embodiments of the present invention also provide a data display system for interactive security, the system comprising:

[0152] The environmental risk assessment module 201 is used to determine the environmental risk weight at the current moment based on the network parameters of the target user in the current device environment collected in real time and the environmental scorer.

[0153] User behavior risk assessment module 202 is used to determine the user behavior risk weight at the current moment based on the user operation profile and real-time collected interaction behavior data of the target user.

[0154] The data evaluation module 203 is used to determine the data sensitivity weight at the current moment based on the sensitivity level of the data to be displayed at the current moment.

[0155] The comprehensive weight determination module 204 is used to determine the comprehensive weight based on environmental risk weight, user behavior risk weight, and data sensitivity weight, and to determine the fuzziness level of the data to be displayed at the current moment based on the magnitude of the comprehensive weight; the magnitude of the comprehensive weight is positively correlated with the fuzziness level of the data to be displayed.

[0156] The data display module 205 is used to display the data to be displayed at the current time according to the fuzzy strategy corresponding to the determined fuzziness level; the size of the fuzziness level is positively correlated with the preset fuzziness degree of data display in the fuzzy strategy.

[0157] Furthermore, in the data display module 205, the blur strategy corresponding to each blur level is configured as follows: when setting the blur level of data display, different preset processing methods are adopted for different types of sensitive data in the data to be displayed; the preset processing methods include data generalization processing, data segmentation masking processing, text replacement, and layer filters.

[0158] Furthermore, before displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the data display module 205 is also configured to execute:

[0159] Obtain the user-defined fuzziness level for sensitive data in the data to be displayed at the current moment;

[0160] The fuzzy level determined by the comprehensive weight is compared with the user-defined fuzzy level, and the larger fuzzy level is taken as the final fuzzy level.

[0161] Furthermore, when displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the data display module 205 is specifically configured to execute:

[0162] Real-time reading of the blurring strategy corresponding to the current rendering data;

[0163] Determine whether the blurring strategy corresponding to the current rendered data meets the requirements of the blurring strategy corresponding to the determined blur level, and obtain the judgment result;

[0164] If the result is negative, the current rendering data will be forcibly switched to the blur strategy corresponding to the maximum blur level for display.

[0165] Furthermore, during a forced switch, the data display module 205 is configured to execute:

[0166] Use gradient animations or masking layers to gradually increase the blurriness of the currently rendered data.

[0167] Furthermore, the data display system also includes an exit lock processing module. After displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the exit lock processing module is configured to execute:

[0168] Monitor the interactive behavior data of target users collected in real time;

[0169] When the target user is detected to be offline, the blur level of the currently displayed data is increased, and the blur level of the currently displayed data is updated according to the blur strategy corresponding to the increased blur level. Offline status includes window out of focus, tab switching, and no user interaction within a preset time interval.

[0170] Furthermore, when updating the data display status according to the fuzzy strategy corresponding to the increased fuzziness level, the departure lock processing module is specifically configured to execute:

[0171] Based on the blurring strategy corresponding to the improved blur level, the blur level of the currently displayed data is gradually increased using CSS layer animation or canvas layer animation.

[0172] The data display system for interactive security provided in this embodiment of the invention is used to execute the data display method for interactive security described above, and thus can achieve the same effect as the data display method for interactive security described above.

[0173] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0174] Thirdly, embodiments of the present invention also provide an electronic device, which includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. The at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement the data display method for interactive security in embodiments of the present invention.

[0175] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the data display method for interactive security in embodiments of the present invention.

[0176] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state disk (SSD)).

[0177] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions within the technical scope disclosed in the present invention should be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A data display method for interactive security, characterized in that, include: Based on the network parameters of the target user in the current device environment collected in real time, the environmental risk weight at the current moment is determined based on the environmental scorer. Based on the real-time collected interaction behavior data of the target users, the risk weight of user behavior at the current moment is determined according to the user operation profile; Determine the data sensitivity weight at the current moment based on the sensitivity level of the data to be displayed at the current moment; A comprehensive weight is determined based on the environmental risk weight, the user behavior risk weight, and the data sensitivity weight, and the fuzziness level of the data to be displayed at the current moment is determined based on the magnitude of the comprehensive weight. The magnitude of the comprehensive weight is positively correlated with the fuzziness level of the data to be displayed; Based on the fuzzy strategy corresponding to the determined fuzziness level, the data to be displayed at the current moment is displayed; The magnitude of the fuzziness level is positively correlated with the preset fuzziness level of the data display in the fuzziness strategy. When displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the method further includes: Real-time reading of the blurring strategy corresponding to the current rendering data; Determine whether the blurring strategy corresponding to the current rendered data meets the requirements of the blurring strategy corresponding to the determined blur level, and obtain the determination result; If the judgment result is negative, the current rendering data will be forcibly switched to the blur strategy corresponding to the maximum blur level for display. The method further includes: when performing a forced switch, using a gradient animation or a mask layer to gradually increase the display blur of the currently rendered data.

2. The data display method for interactive security according to claim 1, characterized in that, For each blur level, different preset processing methods are used for different types of sensitive data in the data to be displayed when setting the blur level of data display. The preset processing methods include data generalization processing, data segmentation masking processing, text replacement and layer filters.

3. The data display method for interactive security according to claim 1, characterized in that, Before displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the method further includes: Obtain the user-defined fuzziness level for sensitive data in the data to be displayed at the current moment; The fuzzy level determined based on the comprehensive weight is compared with the custom fuzzy level, and the fuzzy level with the larger fuzzy level is taken as the final fuzzy level.

4. The data display method for interactive security according to claim 1, characterized in that, After displaying the data to be displayed at the current moment according to the fuzzy strategy corresponding to the determined fuzziness level, the method further includes: Monitor the interactive behavior data of the target user collected in real time; When the target user is detected to be offline, the blur level of the currently displayed data is increased, and the blur level of the currently displayed data is updated according to the blur strategy corresponding to the increased blur level. The offline state includes window out of focus, tab switching, and no user interaction within a preset time interval.

5. The data display method for interactive security according to claim 4, characterized in that, When updating the display blur level of the currently displayed data according to the blur strategy corresponding to the improved blur level, the method is specifically as follows: Based on the blurring strategy corresponding to the improved blur level, the blur level of the currently displayed data is gradually increased using CSS layer animation or canvas layer animation.

6. A data display system for interactive security, characterized in that, include: The environmental risk assessment module is used to determine the environmental risk weight at the current moment based on the network parameters of the target user in the current device environment collected in real time and the environmental scorer. The user behavior risk assessment module is used to determine the user behavior risk weight at the current moment based on the user operation profile and the real-time collected interaction behavior data of the target user. The data evaluation module is used to determine the data sensitivity weight at the current moment based on the sensitivity level of the data to be displayed at the current moment; The comprehensive weight determination module is used to determine a comprehensive weight based on the environmental risk weight, the user behavior risk weight, and the data sensitivity weight, and to determine the fuzziness level of the data to be displayed at the current moment based on the magnitude of the comprehensive weight. The magnitude of the comprehensive weight is positively correlated with the fuzziness level of the data to be displayed; The data display module is used to display the data to be displayed at the current time according to the fuzziness strategy corresponding to the determined fuzziness level; the magnitude of the fuzziness level is positively correlated with the preset data display fuzziness degree in the fuzziness strategy; The data display module is specifically configured to execute: Real-time reading of the blurring strategy corresponding to the current rendering data; Determine whether the blurring strategy corresponding to the current rendered data meets the requirements of the blurring strategy corresponding to the determined blur level, and obtain the determination result; If the judgment result is negative, the current rendering data will be forcibly switched to the blur strategy corresponding to the maximum blur level for display. During a forced switch, the data display module is also configured to execute: Use gradient animations or masking layers to gradually increase the blur level of the currently rendered data.

7. An electronic device, characterized in that, The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the data display method for interactive security as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or instruction set is loaded and executed by a processor to implement the data display method for interactive security as described in any one of claims 1-5.

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