Safety appeal scoring method, safety suggestion pushing method and related device

Abstract

The application discloses a safety appeal scoring method, a safety suggestion pushing method and related devices. The method comprises the following steps: acquiring at least one behavior data of a user operating an electronic device; wherein the behavior data is related to a safety function of the electronic device; scoring each behavior data to obtain an initial safety appeal score; and fusing at least one initial safety appeal score to obtain a final safety appeal score. Through the above method, the safety protection consciousness of the user is objectively measured, and the core basis for actively providing the intelligent and personalized safety protection suggestions for the user is provided.

Description

Technical Field

[0001] This application relates to the field of equipment safety technology, and in particular to scoring methods for safety claims, methods for pushing safety recommendations, and related devices. Background Technology

[0002] As electronic devices become increasingly intelligent, more and more devices offer features that protect user security and privacy, such as privacy avatars, app locks, authentication for externally sourced applications, and phone clones. However, these security and privacy protection features are often deeply embedded and scattered throughout the phone's system. Users need to actively discover, understand, and learn how to configure these features to protect their security and privacy.

[0003] In order to enhance users' awareness of security and privacy features, related technologies provide simple push notifications and introductions to security and privacy features. Summary of the Invention

[0004] This application provides a scoring method for security concerns, a method for pushing security suggestions, and related devices to objectively measure users' security awareness and provide a core basis for intelligent and personalized proactive provision of security protection suggestions to users.

[0005] In a first aspect, this application provides a method for scoring security claims, the method comprising: acquiring at least one behavioral data of a user operating an electronic device; wherein the behavioral data is related to the security functions of the electronic device; scoring each behavioral data to obtain an initial security claim score; and fusing at least one initial security claim score to obtain a final security claim score.

[0006] Secondly, this application provides a security suggestion push method applied to a server. The method includes: receiving a trigger command from a target application sent by an electronic device; obtaining a security request score corresponding to the electronic device; wherein the security request score is a final security request score obtained according to the method in the first aspect; and pushing relevant security suggestions to the electronic device based on the security request score.

[0007] Thirdly, this application provides a security suggestion push method applied to an electronic device. The method includes: in response to a target application being triggered, sending a triggering instruction to a server to enable the server to obtain a security request score corresponding to the electronic device, and determining relevant security suggestions based on the security request score; wherein the security request score is the final security request score obtained according to the method of the first aspect; and receiving security suggestions pushed by the server.

[0008] Fourthly, this application provides an electronic device including a processor and a memory coupled to the processor; wherein the memory is used to store a computer program, and the processor is used to execute the computer program to implement the methods provided in the first, second, or third aspects.

[0009] Fifthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods provided in the first, second, or third aspects.

[0010] The beneficial effects of this application are as follows: Unlike the prior art, the security request scoring method, security suggestion push method, and related device provided in this application obtain at least one behavioral data of a user operating an electronic device; wherein, the behavioral data is related to the security functions of the electronic device; each behavioral data is scored to obtain an initial security request score; and the final security request score is obtained by merging at least one initial security request score. This objectively measures the user's security awareness and provides a core basis for intelligently and personally providing users with proactive security protection suggestions. Furthermore, it can realize the intelligent push of security suggestions to electronic devices based on the security request score, making the security suggestion push more in line with the security awareness of electronic device users. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0012] Figure 1 This is a flowchart illustrating an embodiment of the security claim scoring method provided in this application;

[0013] Figure 2 This is a flowchart illustrating another embodiment of the scoring method for security claims provided in this application;

[0014] Figure 3 This is a flowchart illustrating another embodiment of the scoring method for security claims provided in this application;

[0015] Figure 4 This is a flowchart illustrating an embodiment of the method for determining the calibration function provided in this application;

[0016] Figure 5 This is a flowchart illustrating an embodiment of the security suggestion push method provided in this application;

[0017] Figure 6 This is a flowchart illustrating another embodiment of the security suggestion push method provided in this application;

[0018] Figure 7 This is a schematic diagram of the structure of an embodiment of the electronic device provided in this application;

[0019] Figure 8 This is a schematic diagram of another embodiment of the electronic device provided in this application;

[0020] Figure 9 This is a schematic diagram of an embodiment of the computer-readable storage medium provided in this application. Detailed Implementation

[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It is understood that the specific embodiments described herein are only for explaining this application and not for limiting it. Furthermore, it should be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all structures. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] As electronic devices become increasingly intelligent, more and more devices offer features that protect user security and privacy, such as privacy avatars, app locks, authentication for externally sourced applications, and phone clones. However, these security and privacy protection features are often deeply embedded and scattered throughout the phone's system. Users need to actively discover, understand, and learn how to configure these features to protect their security and privacy.

[0024] In order to enhance users' awareness of security and privacy features, related technologies provide simple push notifications and introductions to security and privacy features.

[0025] The inventors of this application discovered that different users have varying levels of awareness regarding security and privacy protection when using electronic devices, and their priorities differ between security settings and ease of use. Based on this, this application proposes a scoring method that quantifies user security needs based on user behavior data on electronic devices. This method objectively measures users' security awareness and provides a core basis for intelligently and personally providing users with proactive privacy protection suggestions.

[0026] See Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the security claim scoring method provided in this application. The method includes:

[0027] Step 11: Obtain at least one behavioral data of the user operating the electronic device.

[0028] Among these, behavioral data is related to the security functions of electronic devices.

[0029] In some embodiments, the electronic device may be a mobile terminal, such as a smartphone or tablet, or a wearable device, such as a smartwatch. Specifically, the electronic device may be a device with an operating system and communication capabilities.

[0030] Taking mobile devices as an example, mobile devices have many applications installed. Each application performs a corresponding function. For example, financial applications can assist users in investing in financial products. Music applications can provide audio and video resources. Management applications can assist users in managing their mobile devices, such as uninstalling applications, installing applications, scanning for viruses and / or junk files, etc.

[0031] The use of these applications involves security and privacy. Therefore, terminal devices provide corresponding security features, such as harassment blocking, app locking and / or app cloning, authentication of applications installed from external sources, and system cloning, to protect user security and privacy.

[0032] Therefore, user behavior data is recorded when a user operates an electronic device. This application acquires behavioral data related to security functions. In this application, behavioral data related to security functions refers to behavioral data that indicates a security problem after operation, or that requires security protection to improve security.

[0033] In some embodiments, the aforementioned behavioral data includes at least one of the following: launching a security application, clicking a virus scan, tagging a phone number, triggering payment protection, launching a financial application, setting a harassment blocking switch, and setting a push notification switch.

[0034] Step 12: Score each behavioral data point to obtain an initial security requirement score.

[0035] In some embodiments, each behavioral data is scored according to a corresponding scoring function to obtain an initial security requirement score.

[0036] Step 13: Combine at least one initial security claim score to obtain the final security claim score.

[0037] In some embodiments, at least one initial security claim score may be summed, and the summed score may be used as the final security claim score.

[0038] In some embodiments, at least one initial security claim score may be weighted and averaged, and the resulting weighted average score may be used as the final security claim score.

[0039] In some embodiments, at least one initial security claim score may be averaged, and the averaged score may be used as the final security claim score.

[0040] The final security appeal score reflects the user's level of willingness to comply with security requirements for that electronic device. A high final security appeal score indicates a high level of willingness to comply, while a low score indicates a low level of willingness. When pushing security recommendations, the score can be used to determine whether to push such recommendations. If a high final security appeal score indicates a high level of willingness to comply, then security recommendations will be pushed; if a low score indicates a low level of willingness to comply, then security recommendations will not be pushed, or the number of recommended security features in the recommendations will be reduced.

[0041] In this embodiment, by acquiring at least one behavioral data of a user operating an electronic device, wherein the behavioral data is related to the security functions of the electronic device, scoring each behavioral data to obtain an initial security request score, and fusing at least one initial security request score to obtain a final security request score, the user's security awareness is objectively measured. This provides a core basis for intelligently and personally providing users with proactive security protection suggestions. Furthermore, the security suggestion push for electronic devices can be intelligently implemented based on the security request score, making the security suggestion push more in line with the security awareness of electronic device users.

[0042] See Figure 2 , Figure 2 This is a flowchart illustrating another embodiment of the security claim scoring method provided in this application. The method includes:

[0043] Step 21: Obtain at least one behavioral data of the user operating the electronic device.

[0044] Among these, behavioral data is related to the security functions of electronic devices.

[0045] Step 22: Obtain at least one behavioral feature based on each behavioral data point.

[0046] In some embodiments, each behavioral data may be processed to obtain at least one behavioral feature.

[0047] In one application scenario, each piece of behavioral data has a corresponding generation time. Therefore, the first behavioral feature can be the quantity of behavioral data within a preset time period, and the second behavioral feature can be the usage time of that behavioral data within the preset time period. Alternatively, the third behavioral feature can be the time interval between the last behavioral data within the preset time period and the current time.

[0048] Behavioral features are extracted based on the specific behaviors in the behavioral data.

[0049] Step 23: Obtain an initial security appeal score using at least one behavioral characteristic.

[0050] In some embodiments, an initial security requirement score is obtained by comprehensively scoring at least one behavioral feature of each behavioral data according to the corresponding scoring function.

[0051] Step 24: Combine at least one initial security claim score to obtain the final security claim score.

[0052] In this embodiment, by acquiring at least one behavioral data of a user operating an electronic device, wherein the behavioral data is related to the security functions of the electronic device; at least one behavioral feature is obtained based on each behavioral data; an initial security request score is obtained using the at least one behavioral feature; and a final security request score is obtained by fusing the at least one initial security request score, the user's security awareness is objectively measured. This provides a core basis for intelligently and personally providing users with proactive security protection suggestions. Furthermore, the intelligent push of security suggestions to electronic devices can be realized based on the security request score, making the push of security suggestions more in line with the security awareness of electronic device users.

[0053] See Figure 3 , Figure 3 This is a flowchart illustrating another embodiment of the security claim scoring method provided in this application. The method includes:

[0054] Step 31: Obtain at least one behavioral data of the user operating the electronic device.

[0055] Among these, behavioral data is related to the security functions of electronic devices.

[0056] Step 32: Score each behavioral data point to obtain an initial security requirement score.

[0057] Steps 31 to 32 have the same or similar technical solutions as any embodiment of this application, and will not be described in detail here.

[0058] Step 33: Calibrate at least one initial security claim score using a calibration function; wherein the calibration function is related to the activation rate of security functions.

[0059] In this embodiment, considering that the initial security score and security function calculated at this time are not actually on the same dimension, a calibration function related to the activation rate of security function is used to calibrate at least one initial security demand score, so that the calibrated security demand score and security function are on the same dimension, which can better reflect the level of security demand of electronic device users.

[0060] Step 34: Combine at least one initial security claim score after calibration to obtain the final security claim score.

[0061] In some embodiments, at least one initial security claim score after calibration can be summed, and the summed score can be used as the final security claim score.

[0062] In some embodiments, at least one initial security claim score after calibration can be weighted and averaged, and the score obtained after weighted averaging can be used as the final security claim score.

[0063] In some embodiments, at least one initial security claim score after calibration can be averaged, and the averaged score can be used as the final security claim score.

[0064] In one application scenario, refer to Figure 4 The calibration function described above is obtained in the following way:

[0065] Step 41: Determine the activation rate of security functions corresponding to each initial security requirement score, as well as the score range.

[0066] Each scoring range corresponds to the activation rate of a security feature. In other words, each behavioral data point corresponds to the activation rate of a security feature.

[0067] Step 42: Obtain the calibration baseline score using the opening rate.

[0068] In some embodiments, the activation rate is input into the corresponding function to obtain the calibration baseline score.

[0069] In some embodiments, the input can be entered into the corresponding function based on the opening rate. For example, if the opening rate is within a preset range, it is entered into the first function; if the opening rate is outside the preset range, it is entered into the second function.

[0070] Step 43: Obtain the calibration interval using the calibration benchmark score.

[0071] Furthermore, after obtaining the calibration baseline score, the corresponding calibration interval is determined. For example, the calibration interval is obtained by adding or subtracting the corresponding values ​​from the calibration baseline score. That is, the two values ​​obtained by adding or subtracting the corresponding data values ​​from the calibration baseline score are used as the endpoints of the calibration interval.

[0072] Step 44: Use the scoring interval and calibration interval to determine the parameter values ​​in the calibration function, and obtain the calibration function.

[0073] Since the parameter values ​​in the calibration function are not determined, it is necessary to use the scoring interval and calibration interval to determine the parameter values ​​in the calibration function, and then obtain the calibration function corresponding to each row of data.

[0074] In one application scenario, behavioral data includes: launching security applications, clicking on virus scans, tagging phone numbers, triggering payment protection, launching financial applications, setting harassment blocking switches, and setting push notification switches. When the electronic device is a smartphone, the security applications can be phone management apps and / or mobile security guards, etc. It's understood that security applications generally have virus scanning capabilities, which users can enable by clicking the corresponding module. Number tagging can involve tagging existing phone numbers on the smartphone or tagging unknown numbers, such as tagging as harassment calls, scam calls, delivery / food delivery calls, advertising / telemarketing calls, real estate agents, insurance / financial services, taxis, or any other custom tag. Push notification switches can be advertising push notification switches.

[0075] Therefore, it is possible to obtain the user's behavior when operating electronic devices, including the launch behavior of security applications, the click behavior of virus scanning, the behavior of number tagging, the triggering behavior of payment protection, the launch behavior of financial applications, the setting behavior of harassment blocking switches, and the setting behavior of push notification switches.

[0076] Based on the startup behavior of security applications, the click behavior of virus scanning, the behavior of number tagging, the triggering behavior of payment protection, the startup behavior of financial applications, the setting behavior of harassment blocking switch, and the setting behavior of push switch, feature derivation is performed to obtain the features of each behavior.

[0077] Specifically, the first feature derived from the startup behavior of security applications is the number of days the security application has been launched within a preset time period; this preset time period can be 30 days, 60 days, 90 days, or 120 days. The specific time period is calculated backwards from the current time. For example, if the preset time period is 90 days, then the first feature is the number of days the security application has been launched within the last 90 days. The second feature is the average daily number of launches of the security application within the preset time period. The third feature is the number of days since the most recent launch of the security application within the preset time period.

[0078] The first feature derived from the click behavior of virus scanning is the number of days the virus scan was clicked within a preset time period. The second feature is the average daily number of clicks for the virus scan within the preset time period. The third feature is the number of days since the most recent launch of the virus scan within the preset time period.

[0079] The first feature derived from the number tagging behavior is the number of days the phonebook number was tagged within a preset time period. The second feature is the average daily number of times the phonebook number was tagged within the preset time period. The third feature is the number of days since the most recent tagging of the phonebook number within the preset time period.

[0080] The first characteristic derived from the payment protection triggering behavior is the number of days payment protection was triggered within a preset time period. The second characteristic is the average daily number of payment protection triggers within the preset time period. The third characteristic is the number of days since the most recent payment protection trigger within the preset time period. The fourth characteristic is the number of applications that triggered payment protection within the preset time period.

[0081] The first feature derived from the launch behavior of financial applications is the number of days the financial application was launched within a preset time period; the second feature is the average number of launches of the financial application per day within the preset time period; and the third feature is the number of days since the most recent launch of the financial application within the preset time period.

[0082] The first characteristic derived from the behavior of setting up the harassment blocking switches is the number of times the four blocking switches for suspected fraud, harassing calls, advertising and sales, and real estate agents are turned on.

[0083] The first feature derived from the settings behavior of the push switch is whether the push switch is currently turned on.

[0084] The initial security requirement score is obtained by using the corresponding scoring function to score the security requirement of the above-mentioned security application startup behavior, virus scan click behavior, number tagging behavior, payment protection trigger behavior, financial application startup behavior, harassment blocking switch setting behavior, and push switch setting behavior.

[0085] Specifically, the scoring method for the startup behavior of security applications is as follows:

[0086] Step 1: First, encode the startup behavior of security applications based on three characteristics, ranging from 0 to 10, using the following formula:

[0087]

[0088] Where a1 represents the first characteristic corresponding to the startup behavior of the security application, b1 represents the second characteristic corresponding to the startup behavior of the security application, c1 represents the third characteristic corresponding to the startup behavior of the security application, and 90 represents the preset time in days.

[0089] Step 2: Then use the encoded value codeV1 as the input to the scoring function to obtain the corresponding initial security requirement score1.

[0090]

[0091] Specifically, the scoring method for click behavior during virus scanning is as follows:

[0092] Step 1: First, encode the three characteristics of the click behavior detected by the virus scan, with a range of 0-10.

[0093]

[0094] Where a2 represents the first feature corresponding to the click behavior of virus scanning, b2 represents the second feature corresponding to the click behavior of virus scanning, c2 represents the third feature corresponding to the click behavior of virus scanning, and 90 represents the preset time in days.

[0095] Step 2: Then use the encoded value codeV2 as the input to the scoring function to obtain the corresponding initial security requirement score2.

[0096]

[0097] Specifically, the scoring method for number tagging behavior is as follows:

[0098] Step 1: First, encode the number marking behavior based on 3 characteristics, with a range of 0-10.

[0099]

[0100] Where a3 represents the first feature corresponding to the number marking behavior, b3 represents the second feature corresponding to the number marking behavior, c3 represents the third feature corresponding to the number marking behavior, and 90 represents the preset time in days.

[0101] Step 2: Then use the encoded value codeV3 as the input to the scoring function to obtain the corresponding initial security requirement score score3.

[0102]

[0103] Specifically, the scoring method for payment protection trigger behaviors is as follows:

[0104] Step 1: First, encode the three features of the payment protection trigger behavior, with a range of 0-10.

[0105]

[0106] Where a4 represents the first feature corresponding to the payment protection triggering behavior, b4 represents the second feature corresponding to the payment protection triggering behavior, c4 represents the third feature corresponding to the payment protection triggering behavior, and 90 represents the preset time in days.

[0107] Step 2: Then use the encoded value codeV4 as the input to the scoring function to obtain the security appeal score score4.

[0108]

[0109] Step 3: Encode the behavior based on the fourth feature of the payment protection trigger and the score obtained in Step 2, with a range of 0-10.

[0110]

[0111] d represents the fourth characteristic that triggers payment protection behavior. The relationship between the d value and scoreThreshold is shown in the table below:

[0112] 1 40 2 60 3 70 4 60 [5,8] 50 9 40 10 50

[0113] Step 4: Use the encoded value from Step 3 as input to the scoring function to obtain the corresponding initial security requirement score, score5.

[0114]

[0115] Specifically, the scoring method for the launch behavior of financial applications is as follows:

[0116] Step 1: First, encode the three characteristics of the startup behavior of financial applications, with a range of 0-10.

[0117]

[0118] Where a6 represents the first characteristic corresponding to the startup behavior of the financial application, b6 represents the second characteristic corresponding to the startup behavior of the financial application, c6 represents the third characteristic corresponding to the startup behavior of the financial application, and 90 represents the preset time in days.

[0119] Step 2: Then use the encoded value as input to the scoring function to obtain the corresponding initial security requirement score6.

[0120]

[0121] Specifically, the scoring method for the setting behavior of the harassment blocking switch is as follows:

[0122] Step 1: Encode the first characteristic of the harassment blocking switch setting behavior according to the following formula.

[0123]

[0124] Here, a7 represents the first feature corresponding to the setting behavior of the harassment blocking switch.

[0125] Step 2: Then use the encoded value as input to the scoring function to obtain the corresponding initial security requirement score of score7.

[0126]

[0127] Specifically, the scoring method for the push notification switch setting behavior is as follows:

[0128] Step 1: Encode the first feature of the push switch setting behavior using the following formula.

[0129]

[0130] Where 'a' represents the first feature corresponding to the setting behavior of the push switch.

[0131] Step 2: Then use the encoded value as input to the scoring function to obtain the corresponding initial security requirement score, score8.

[0132]

[0133] Based on this, the initial security requirement scores for the above 7 types of behaviors all range from 0 to 100.

[0134] Cross-analysis of the initial security demand scores and security function activation behaviors for the seven categories revealed that the activation rates of security functions differed within the same score range. This indicates that although the initial security demand scores for the seven categories of behaviors were the same, they expressed different subjective intentions regarding security demands. Therefore, score calibration was performed to ensure that the same score described the same subjective intention regarding security demands.

[0135] Security features are a type of security and privacy characteristic, and their activation, to a certain extent, represents a user's subjective willingness to prioritize security and privacy. In subsequent security recommendation processes, the user's choice of security feature settings will serve as an objective verification basis and an anchor target for scoring and calibration.

[0136] The calibration process is as follows:

[0137] Step 1: First, obtain the calibration baseline score according to the following calibration formula.

[0138]

[0139] The ratio represents the activation rate of security features in the segment corresponding to the initial security appeal scores for the seven types of behaviors. Specifically, a ratio of 0.025 corresponds to a score of 45.

[0140] When the ratio is less than or equal to 0.025, increasing the ratio by 1.1 times will increase the score by 5 points.

[0141] When the ratio is greater than 0.025, the ratio increases by 1.1 times, and the score increases by 3.5 points.

[0142] Step 2: Based on the calibration baseline score, add or subtract adjustment points to obtain the calibration range.

[0143] The adjustment range for each scoring interval is shown in the table below:

[0144] 0-20 Add or subtract 4.5 from the calibration baseline score. 20-40 The calibration baseline score is increased or decreased by 4.0. 40-50 Add or subtract 3.5 from the calibration baseline score. 50-60 Add or subtract 3.0 from the calibration baseline score. >＝60 Add or subtract 2.0 from the calibration baseline score.

[0145] Step 3: Based on the linear function y = a*x + b, map the original scoring interval to the calibration interval.

[0146] Example of calibration process:

[0147] Suppose a user's electronic device has an initial security appeal score of 68.5 for the launch behavior of security applications, with a score range of >= 60. The activation rate ratio of security functions within this score range is 4.73%. Based on the calibration formula and adjustment score, the calculated calibration baseline score is 68.416, and the calibration range is [66.416, 70.416]. Using a linear function, the original score range [60, 100] is mapped to the calibration range [66.416, 70.416], allowing us to calculate the mapping parameters a and b, and thus obtain the calibration function corresponding to each type of behavior data. This calibration function can then be used to score the initial security appeal.

[0148] It is understandable that the calibration function for each type of behavioral data can be obtained using its respective initial security requirement score.

[0149] Furthermore, after calibrating the initial security appeal scores, the initial security appeal scores for each type of behavior after calibration are averaged and summed, or the top N initial security appeal scores (sorted by score from highest to lowest) are averaged and summed to obtain the final security appeal score, which can be calculated using the following formula:

[0150]

[0151] In this embodiment, the security awareness of users corresponding to electronic devices is objectively measured through the above-mentioned methods, providing a core basis for providing users with intelligent and personalized security protection suggestions. Furthermore, the intelligent push of security suggestions to electronic devices can be realized based on the security demand score, making the push of security suggestions more in line with the security awareness of electronic device users.

[0152] See Figure 5 , Figure 5 This is a flowchart illustrating an embodiment of the security suggestion push method provided in this application. Applied to a server, the method includes:

[0153] Step 51: Receive the trigger command from the target application sent by the electronic device and obtain the security requirement score corresponding to the electronic device.

[0154] The security appeal score is the final security appeal score obtained according to the method described in any of the above embodiments.

[0155] In some embodiments, the security appeal score may be updated periodically using behavioral data related to security features.

[0156] Step 52: Push relevant security recommendations to electronic devices based on the security requirement score.

[0157] See Figure 6 , Figure 6This is a flowchart illustrating an embodiment of the security suggestion push method provided in this application. Applied to electronic devices, the method includes:

[0158] Step 61: In response to the target application being triggered, a trigger command is sent to the server so that the server can obtain the security request score corresponding to the electronic device and determine relevant security recommendations based on the security request score.

[0159] The security appeal score is the final security appeal score obtained according to the method described in any of the above embodiments.

[0160] Step 62: Receive security advice pushed by the server.

[0161] Furthermore, in some application scenarios, after receiving security recommendations pushed by the server, the security recommendations are displayed; in response to the confirmation command for the security recommendations, detailed information about the security recommendations and the corresponding settings jump guide are displayed.

[0162] In some application scenarios, after receiving security advice pushed by the server, the security advice is displayed; in response to the confirmation command for the security advice, the user is redirected to the settings interface corresponding to the security advice.

[0163] In one application scenario, users can receive security advice by clicking on the interface of a business application, such as a mobile phone manager or security assistant, using their electronic devices.

[0164] Specifically, users can trigger a smart suggestion request by clicking on the relevant functional modules of a business application on their electronic devices, thereby interacting with the business application and the security suggestion client.

[0165] Upon receiving the request, the security advice client activates the relevant functions and sends a request for intelligent advice to the security advice server.

[0166] When the server receives the request, the cloud engine makes an intelligent decision. The decision is based on the security requirement score of the user corresponding to the electronic device, which is quantified by any of the above embodiments. Based on the security requirement score, the server makes intelligent suggestions on whether to recommend security functions and which security functions to recommend.

[0167] Intelligent suggestion messages are uploaded from the server to the client and then displayed to the user. When the user gives positive feedback on the electronic device, the intelligent suggestion will introduce the recommended security features and settings redirection to the user.

[0168] Among them, the intelligent security feature recommendation service provides users with intelligent and personalized recommendation services. The key point is the user security and privacy demand profile scoring calculation engine, which provides a quantitative method for security and privacy demand scoring. It quantifies each user's subjective willingness to meet security and privacy demands into an objective score, providing a basis for intelligent recommendation decisions.

[0169] See Figure 7 , Figure 7 This is a schematic diagram of an embodiment of the electronic device provided in this application. The electronic device 110 includes a processor 111 and a memory 112 coupled to the processor 111; wherein the memory 112 is used to store a computer program, and the processor 111 is used to execute the computer program to implement the following method:

[0170] Acquire at least one type of behavioral data of a user operating an electronic device; wherein the behavioral data is related to the security functions of the electronic device; score each type of behavioral data to obtain an initial security request score; and fuse at least one initial security request score to obtain a final security request score.

[0171] Alternatively, it can receive trigger commands from the target application sent by the electronic device, obtain the security requirement score corresponding to the electronic device, and push relevant security suggestions to the electronic device based on the security requirement score.

[0172] Alternatively, in response to the target application being triggered, a trigger command is sent to the server so that the server can obtain the security request score corresponding to the electronic device and determine relevant security recommendations based on the security request score; and the server can receive security recommendations pushed by the server.

[0173] It is understood that the processor 111 is used to execute computer programs to implement the methods of any of the above embodiments.

[0174] See Figure 8 , Figure 8 This is a schematic diagram of another embodiment of the electronic device provided in this application. The electronic device 110 may be, for example, a mobile electronic device, and may include: a memory 112, a processor (Central Processing Unit, CPU) 111, a circuit board (not shown), a power supply circuit, and a microphone 123. The circuit board is disposed inside the space enclosed by the housing; the processor 111 and the memory 112 are disposed on the circuit board; the power supply circuit is used to supply power to the various circuits or devices of the electronic device; the memory 112 is used to store executable program code; the processor 111 runs a computer program corresponding to the executable program code by reading the executable program code stored in the memory 112, to implement the method of any of the above embodiments.

[0175] The electronic device may also include: peripheral interface 114, RF (Radio Frequency) circuit 116, audio circuit 117, speaker 122, power management chip 119, input / output (I / O) subsystem 120, other input / control devices 121, display 124, and external port 115. These components communicate via one or more communication buses or signal lines 118.

[0176] The memory 112 can be accessed by the processor 111, peripheral interface 114, etc. The memory 112 may include high-speed random access memory, and may also include non-volatile memory, such as one or more disk storage devices, flash memory devices, or other volatile solid-state storage devices. The peripheral interface 114 can connect the device's input and output peripherals to the processor 111 and the memory 112.

[0177] The I / O subsystem 120 can connect input / output peripherals on the device, such as a display 124 and other input / control devices 121, to the peripheral interface 114. The I / O subsystem 120 may include a display controller 1201 and one or more input controllers 1202 for controlling other input / control devices 121. The one or more input controllers 1202 receive or send electrical signals to other input / control devices 121, which may include physical buttons (press buttons, rocker buttons, etc.), dial pads, slide switches, joysticks, and click wheels. It is worth noting that the input controllers 1202 can be connected to any of the following: a keyboard, an infrared port, a USB interface, and a pointing device such as a mouse.

[0178] The display 124 is an input and output interface between the user's electronic device and the user, displaying visual output to the user. The visual output may include graphics, text, icons, videos, etc.

[0179] The display controller 1201 in the I / O subsystem 120 receives or sends electrical signals to the display 124. The display 124 detects touch on the touchscreen, and the display controller 1201 converts the detected touch into interaction with user interface objects displayed on the display 124, thus realizing human-computer interaction. The user interface objects displayed on the display 124 can be icons for running games, icons for connecting to a network, etc.

[0180] The RF circuit 116 is primarily used to establish communication between the mobile phone and the wireless network (i.e., the network side), enabling the mobile phone to receive and send data with the wireless network. Examples include sending and receiving SMS messages and emails. Specifically, the RF circuit 116 receives and transmits RF signals, also known as electromagnetic signals. The RF circuit 116 converts electrical signals into electromagnetic signals or vice versa, and uses these electromagnetic signals to communicate with the communication network and other devices. The RF circuit 116 may include known circuits for performing these functions, including but not limited to antenna systems, RF transceivers, one or more amplifiers, tuners, one or more oscillators, digital signal processors, CODEC (Coder-Coder) chipsets, Subscriber Identity Modules (SIMs), etc.

[0181] The audio circuit 117 is mainly used to receive audio data from the peripheral interface 114, convert the audio data into electrical signals, and send the electrical signals to the speaker 122. The speaker 122 is used to convert the voice signals received by the mobile phone from the wireless network via the RF circuit 116 back into sound and play the sound to the user. The power management chip 119 is used to provide power and power management for the processor 111, the I / O subsystem 120, and the hardware connected to the peripheral interface 114.

[0182] The aforementioned electronic devices can be mobile terminals, such as smartphones and tablets, or terminal devices, such as personal computers.

[0183] See Figure 9 , Figure 9 This is a schematic diagram of an embodiment of the computer-readable storage medium provided in this application. The computer-readable storage medium 150 stores a computer program 151, which, when executed by a processor, implements the following method:

[0184] Acquire at least one type of behavioral data of a user operating an electronic device; wherein the behavioral data is related to the security functions of the electronic device; score each type of behavioral data to obtain an initial security request score; and fuse at least one initial security request score to obtain a final security request score.

[0185] Alternatively, it can receive trigger commands from the target application sent by the electronic device, obtain the security requirement score corresponding to the electronic device, and push relevant security suggestions to the electronic device based on the security requirement score.

[0186] Alternatively, in response to the target application being triggered, a trigger command is sent to the server so that the server can obtain the security request score corresponding to the electronic device and determine relevant security recommendations based on the security request score; and the server can receive security recommendations pushed by the server.

[0187] It is understood that when computer program 151 is executed by a processor, it can also implement the methods of any of the above embodiments.

[0188] In summary, the security request scoring method, security suggestion push method, and related apparatus provided in this application objectively measure the user's security awareness by acquiring at least one behavioral data of the user operating the electronic device; wherein the behavioral data is related to the security functions of the electronic device; scoring each behavioral data to obtain an initial security request score; and merging at least one initial security request score to obtain a final security request score. This provides a core basis for intelligently and personally providing users with proactive security protection suggestions. Furthermore, it enables intelligent security suggestion push to electronic devices based on the security request score, making the security suggestion push more in line with the security awareness of electronic device users.

[0189] In other words, this application objectively quantifies the security and privacy needs of users of electronic devices and distinguishes the differences in security and privacy needs among users of each electronic device.

[0190] Furthermore, the effectiveness of the objective and quantifiable security demand score provides a key basis for security recommendation decisions. By reaching the business application entry point, it proactively, intelligently, and personally provides users with security and privacy feature recommendation services and setup guides, broadening users' awareness of security and privacy features while reducing interference for users with low security and privacy demands and lowering the learning cost for users to understand and set up security and privacy features.

[0191] In the several embodiments provided in this application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0192] If the integrated units in the other embodiments described above are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0193] The above description is merely an embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for scoring security claims, characterized in that, The method includes: Acquire at least one type of behavioral data related to a user's operation of an electronic device; wherein the behavioral data is related to the security functions of the electronic device; Each behavioral data point is scored to obtain an initial security requirement score. The at least one initial security claim score is calibrated using a calibration function; wherein the calibration function is related to the activation rate of the security function; The final security requirement score is obtained by integrating at least one initial security requirement score after calibration. The calibration function is obtained in the following way: Determine the activation rate of the security function corresponding to each initial security requirement score, and the score range; The calibration baseline score is obtained using the aforementioned opening rate; The calibration interval is obtained using the calibration reference score; The parameter values ​​in the calibration function are determined using the scoring interval and the calibration interval, thus obtaining the calibration function.

2. The scoring method according to claim 1, characterized in that, The process of scoring each behavioral data point to obtain an initial security requirement score includes: At least one behavioral feature is obtained based on each of the behavioral data; The initial security appeal score is obtained using at least one of the behavioral characteristics.

3. The scoring method according to claim 1, characterized in that, The behavioral data includes at least one of the following: launching security applications, clicking virus scans, number tagging, triggering payment protection, launching financial applications, setting harassment blocking switches, and setting push notification switches.

4. A method for pushing security suggestions, characterized in that, Applied to a server, the method includes: Receive a trigger command from a target application sent by an electronic device, and obtain a security request score corresponding to the electronic device; wherein the security request score is a final security request score obtained according to the method described in any one of claims 1-3; Based on the security requirement score, relevant security recommendations are pushed to the electronic device.

5. A method for pushing security suggestions, characterized in that, Applied to electronic devices, the method includes: In response to the target application being triggered, a trigger command is sent to the server so that the server obtains the security request score corresponding to the electronic device and determines relevant security recommendations based on the security request score; wherein, the security request score is the final security request score obtained according to the method described in any one of claims 1-3; Receive the security recommendations pushed by the server.

6. The method according to claim 5, characterized in that, After receiving the security advice pushed by the server, the process includes: Show the security recommendations mentioned above; In response to the confirmation command for the security recommendation, display detailed information about the security recommendation and corresponding settings navigation instructions, or... In response to the confirmation command for the security recommendation, the user is redirected to the settings interface corresponding to the security recommendation.

7. An electronic device, characterized in that, The electronic device includes a processor and a memory coupled to the processor; The memory is used to store a computer program, and the processor is used to execute the computer program to implement the method as described in any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1-6.

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