Access Control Management Method and System Based on Virtual Key Management

Abstract

This invention relates to the field of computer technology, and more particularly to an access control management method and system based on virtual key management. First, the initial attributes of the virtual key, user historical data, and real-time requests are acquired to form initial parameters. Next, these parameters are used to generate an initial version of the virtual key, and initial permissions are calculated using a pre-trained machine learning model. Then, the system collects feedback on the initial permissions or adjusts the initial parameters based on environmental data to obtain adjustment results. Based on these adjustment results, the initial permissions are optimized to generate a target version of the virtual key. Finally, the target version is assigned to the user or allowed to claim it independently, and when a user attempts to access the system, permissions are verified based on their identity and the target version. This invention achieves dynamic, intelligent, and flexible access control management.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to an access control management method and system based on virtual key management. Background Technology

[0002] In today's campus management, smart access control devices, including smart locks and smart door sensors, are installed at the entrances of classrooms, offices, dormitories, and other facilities for administrators to enter and exit. As the number of smart devices increases, an access control management system will be built to improve overall management efficiency, enabling unified management of all smart access control devices across the campus and batch authorization of personnel.

[0003] The introduction of access control systems has driven the evolution of access control management towards a more refined approach. Access control systems manage the following dimensions: User dimension: adding all authorized users to the system; Location dimension: adding all smart access control devices to the system; Time dimension: setting the permitted time range for opening the door.

[0004] Based on the information above, in traditional access control / locking devices or management systems, whether a person can open an access control device is usually determined by access permissions, that is, assigning a specific person the right to use an access control device. Combined with time-based settings, this allows a specific person to open the door to a specific space at a specific time. However, in a school setting, this person-based access control method presents several challenges: schools have a large number of people, with some universities having tens of thousands; the types of people in schools are also diverse, including faculty, staff, students, and administrators; schools have numerous access control devices and hundreds of classrooms or functional rooms; and a need for granular daily settings, specifying which times each day are permitted to open doors.

[0005] Addressing the four scenarios mentioned above, implementing granular management of access control permissions within a system becomes extremely complex and inconvenient. This is especially true in scenarios involving frequent dynamic authorization, batch permission adjustments, and temporary cancellation / addition of permissions, where significant time will be spent searching for the access control devices requiring modification. A more convenient and rapid method and system are needed to manage the authorization process of smart access control devices, enabling batch permission management and quick dynamic permission adjustments. Summary of the Invention

[0006] Therefore, the present invention provides an access control permission management method and system based on virtual key management to solve the aforementioned problems existing in the prior art.

[0007] To achieve the above objectives, the present invention provides an access control and permission management method based on virtual key management, comprising:

[0008] Step S1 is used to obtain the initial attributes of the virtual key to obtain initial parameters, including initial ID, initial name, initial status, initial validity period, initial spatial range and initial time period range, and also to obtain the initial number of virtual keys, the user's historical data and the user's real-time request information.

[0009] Step S2: Generate an initial version of the virtual key based on the initial parameters, and perform calculations based on a pre-trained machine learning model to obtain the initial permission result;

[0010] Step S3 is used to collect feedback information related to the initial permission result, or to adjust at least one parameter in the initial parameters based on environmental data to obtain an adjustment result;

[0011] Step S4: Adjust the initial permission result according to the adjustment result to generate the target version of the virtual key;

[0012] Step S5: Assign the target version to the user, or set it to be claimed by the user independently, and verify permissions based on the user and the target version.

[0013] Furthermore, the process of step S1 includes:

[0014] Step S11 is used to obtain the type distribution parameters of school personnel, the spatial distribution density parameters of access control equipment, and the average daily personnel entry and exit time distribution parameters.

[0015] Step S12: Determine the initial number of virtual keys according to the type distribution parameter number, allocate corresponding spatial ranges to access control devices in different areas according to the spatial distribution density parameter to obtain the initial spatial range, and determine the initial time period range according to the entry and exit time period distribution parameter.

[0016] Furthermore, the process of step S12 includes:

[0017] Step S121: Determine the initial quantity based on the type distribution parameters and the preset virtual key base number allocated to each type of personnel;

[0018] Step S122: Identify high-density areas and low-density areas based on the spatial density distribution parameters, and allocate corresponding initial spatial ranges to access control devices in different areas in combination with preset spatial allocation rules;

[0019] Step S123: Determine the initial time range based on the entry and exit time distribution parameters and the preset time allocation rules.

[0020] Furthermore, the process of step S2 includes:

[0021] Step S21: Obtain the user's historical access records according to the initial parameters, and obtain the user's historical abnormal records according to the user's real-time request information;

[0022] Step S22: Using the initial spatial range, the initial time range, the historical access records, and the initial ID as inputs, construct a probability prediction model to predict the probability value of a user accessing each sub-region within the initial spatial range within the initial time range, and obtain the prediction result.

[0023] Step S23: Using the real-time request information and the historical anomaly records as input, construct a risk assessment model to evaluate the risk score of the current request information and obtain the assessment result;

[0024] Step S24: Use the historical access records, the permission change history in the historical data, and the initial parameters as input to build a suggestion model and output optimized suggestions to obtain suggestion results;

[0025] Step S25: Perform a comprehensive analysis based on the prediction results, the evaluation results, and the suggested results to obtain the initial permission results.

[0026] Furthermore, the process of step S25 includes:

[0027] Step S251: Extract the access probability value of each sub-region based on the prediction result, and determine the intensity of user access demand in each sub-region according to the preset probability threshold. Mark the sub-region with the access probability value greater than the probability threshold as the core access region.

[0028] Step S252: The risk scores in the assessment results are graded, and a risk threshold range is set to obtain the risk judgment result, wherein...

[0029] If the risk score is below the first risk threshold, it is determined to be a low-risk request; if the risk score is greater than or equal to the first risk threshold and less than the second risk threshold, it is determined to be a medium-risk request; if the risk score is greater than the second risk threshold, it is determined to be a high-risk request.

[0030] Step S253: Convert the optimization suggestions in the suggested results into parameter adjustment instructions;

[0031] Step S254: Generate an initial permission result based on the core access area, the risk assessment result, and the parameter adjustment instruction.

[0032] Furthermore, the process of step S3 includes:

[0033] Step S31: Collect feedback information related to the initial permission result. The feedback information includes the user's experience with the virtual key permission, the ease of permission application, and the rationality of permission allocation.

[0034] Step S32: Collect environmental data, including changes in personnel flow in the area where the access control device is located, distribution of access time, device operating status, and security incident records;

[0035] Step S33: Analyze the feedback information and the environmental data to determine whether the initial parameters need to be adjusted. If adjustment is required, adjust at least one parameter in the initial parameters according to the preset parameter adjustment rules to obtain the adjustment result.

[0036] Furthermore, the process of step S33 includes:

[0037] Step S331: Quantitatively analyze the feedback information, set a threshold for user experience satisfaction, and adjust the initial parameters when the proportion of negative evaluations in the feedback information exceeds the threshold.

[0038] Step S332: Dynamically monitor the environmental data, set abnormal thresholds for personnel flow, access time, and security events, and adjust the initial parameters when any indicator is detected to exceed the abnormal threshold.

[0039] Step S333: According to the preset parameter adjustment rules, at least one parameter among the initial parameters is adjusted separately or in combination for different types of feedback information and abnormal environmental data situations.

[0040] Furthermore, the process of step S4 includes:

[0041] Step S41: Map and match the adjustment result with the initial permission result to identify the permission items that need to be adjusted to obtain the identification result;

[0042] Step S42: Modify the recognition result according to the adjustment result to obtain the modified result;

[0043] Step S43: Combine the modified result with the unadjusted permission items to generate the target version of the virtual key.

[0044] Furthermore, the process of step S42 includes:

[0045] Step S421: Locate the corresponding permission item in the recognition result according to the parameter modification instruction specified in the adjustment result;

[0046] Step S422: Update the specific parameter values ​​of the permission items located in the identification results according to the modification values ​​or modification rules in the parameter modification instructions; or, calculate them.

[0047] Step S423: Verify whether the modified permission item conforms to the preset permission rules and format requirements;

[0048] Step S424: The modified permission item that has passed verification is determined as the modification result.

[0049] On the other hand, the present invention provides an access control system based on virtual key management, characterized in that it includes:

[0050] The attribute definition module is used to obtain the initial attributes of the virtual key to obtain initial parameters, including initial ID, initial name, initial status, initial validity period, initial spatial range, and initial time period range. It is also used to obtain the initial number of virtual keys, the user's historical data, and the user's real-time request information.

[0051] The version generation module is connected to the attribute definition module. It generates an initial version of the virtual key based on the initial parameters and performs calculations based on a pre-trained machine learning model to obtain the initial permission result.

[0052] A data collection module, connected to the version generation module, is used to collect feedback information related to the initial permission result, or to adjust at least one parameter in the initial parameters based on environmental data to obtain an adjustment result.

[0053] A parameter adjustment module, connected to the data collection module, adjusts the initial permission result according to the adjustment result to generate a target version of the virtual key;

[0054] The permission verification module is connected to the parameter adjustment module, which assigns the target version to the user, or sets it to be claimed by the user independently, and performs permission verification based on the user and the target version.

[0055] Compared with existing technologies, the advantages of this invention are as follows: By using virtual keys to replace traditional physical keys, the risk of key loss or theft is reduced; dynamic access control effectively prevents unauthorized access; permissions are generated by combining real-time requests and historical data analysis to accurately identify abnormal behavior and improve system security; machine learning models are used to comprehensively analyze user behavior, risk assessment, and optimization suggestions to achieve automatic permission adjustment and reduce manual intervention; parameters are dynamically optimized based on feedback and environmental data to continuously improve the rationality of permission allocation; the number and space of virtual keys are allocated as needed to avoid resource waste; and predictive models optimize the efficiency of access control equipment, reducing operating costs.

[0056] In particular, the collected parameters provide rich data support for subsequent dynamic adjustment of permissions and analysis of abnormal behavior, helping to achieve intelligent and refined access control management. Precise permission configuration reduces the cumbersome process of user application and permission adjustment, improves access efficiency, and simultaneously ensures campus security, creating a convenient and safe campus environment. Whether determining the number of virtual keys, spatial range, or time range, the principle of on-demand allocation is followed to ensure that resource investment accurately matches actual needs, avoiding resource idleness or insufficiency.

[0057] In particular, by extracting access probability values ​​and marking core access areas, the system can accurately grasp the user's main activity range, providing strong support for permission configuration in key areas while avoiding over-allocation of permissions and improving the granularity of permission management. Risk scores are graded, enabling the system to adopt differentiated permission control strategies based on different risk levels. Optimization suggestions are translated into specific parameter adjustment instructions, enhancing the executability of the suggestions and ensuring that optimization measures are accurately implemented in permission configuration. This allows for timely improvement and optimization of permission management strategies to adapt to changes in the campus environment and user needs. By comprehensively considering core access areas, risk assessment results, and parameter adjustment instructions, the system effectively balances user needs and security management. While meeting users' reasonable access needs, it effectively controls risks, resulting in more reasonable and reliable initial permission results, providing strong support for the stable operation of the campus access control system.

[0058] In particular, quantifying and analyzing user feedback and setting clear satisfaction thresholds makes the decision-making process more objective, avoids biases in subjective judgment, and ensures that necessary adjustments are only made when user satisfaction declines significantly. Through dynamic monitoring of environmental data and setting anomaly thresholds, the system can identify potential safety risks and operational problems, and adjust parameters in a timely manner to prevent further deterioration and ensure campus safety. Based on preset parameter adjustment rules, the system can flexibly adjust single or combined parameters according to different types of feedback information and abnormal environmental data, ensuring that adjustment measures are precise and effective, and avoiding over- or under-adjustment.

[0059] In particular, by mapping and matching the adjustment results with the initial permission results, the system accurately identifies the permission items that need adjustment, ensuring the targeted nature and effectiveness of the adjustment operations. The modified permission items are organically combined with the unadjusted permission items to form a complete virtual key target version, guaranteeing the comprehensiveness and accuracy of permission configuration. It can quickly locate the permission items that need adjustment, improving adjustment efficiency and shortening response time. It flexibly executes parameter value updates or calculations based on modification instructions, adapting to diverse adjustment needs and enhancing the system's flexibility and adaptability. Through accurate and timely permission adjustments, it ensures that users obtain reasonable access permissions, improving user experience and satisfaction. Attached Figure Description

[0060] Figure 1 A flowchart illustrating the access control and permission management method based on virtual key management provided by this invention;

[0061] Figure 2 This is a flowchart illustrating step S1 in the access control and permission management method based on virtual key management provided by the present invention.

[0062] Figure 3 This is a flowchart illustrating step S2 in the access control and permission management method based on virtual key management provided by the present invention.

[0063] Figure 4 This is a schematic diagram of the access control and access management system based on virtual key management provided by the present invention. Detailed Implementation

[0064] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0065] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0066] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0067] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0068] Please see Figure 1 As shown, the present invention provides an access control permission management method based on virtual key management, comprising:

[0069] Step S1 is used to obtain the initial attributes of the virtual key to obtain initial parameters, including initial ID, initial name, initial status, initial validity period, initial spatial range and initial time period range, and also to obtain the initial number of virtual keys, the user's historical data and the user's real-time request information.

[0070] Specifically, the initial ID assigns a unique identifier to each virtual key. This identifier can be automatically generated randomly by the system or generated according to specific encoding rules (such as combining user information, date, etc.) to ensure accurate differentiation of different virtual keys within the system. The initial name is based on information such as the access control location associated with the virtual key, the usage scenario, or the user group it belongs to, for example, "Office Area - Zhang San's Exclusive Key," facilitating user identification and management. The initial state is set to "Disabled," "Not Enabled," or "Normal," determined based on the access control system's default policy or the administrator's pre-configuration. If the system is newly deployed, most virtual keys are typically initially in the "Disabled" state, and will be enabled as needed after allocation. The system retrieves the user's historical data, querying the user's (or user group's) past successful and failed access records, including access time, location, frequency, and reasons for denial. It also queries the types, scope, and duration of virtual key permissions previously granted to the user, analyzing the user's historical data to identify their access patterns (such as frequently accessed areas and frequently accessed time periods). Finally, it obtains the specific content of the user's access permission requests, such as the area to be accessed, the desired time period, and the purpose of access. Obtain contextual information related to the request, such as when the request was initiated, the urgency of the request, and the type of device that initiated the request.

[0071] Step S2: Generate an initial version of the virtual key based on the initial parameters, and perform calculations based on a pre-trained machine learning model to obtain the initial permission result;

[0072] Step S3 is used to collect feedback information related to the initial permission result, or to adjust at least one parameter in the initial parameters based on environmental data to obtain an adjustment result;

[0073] Step S4: Adjust the initial permission result according to the adjustment result to generate the target version of the virtual key;

[0074] Step S5: Assign the target version to the user, or set it to be claimed by the user independently, and verify permissions based on the user and the target version.

[0075] Specifically, in the access control management system backend, the administrator selects a suitable virtual key from the target version library based on the user's application information, departmental needs, or established permission allocation strategies. This key is then sent to the user's mobile device (such as a mobile phone or smart card). Upon receiving the key, the user automatically installs or activates the virtual key application, completing the allocation process. During allocation, an operation log is recorded, including allocation time, allocation recipient, and virtual key ID, facilitating subsequent traceability and management. The access control system's user self-service platform publishes information on available virtual key target versions, specifying the eligibility requirements (such as identity authentication and completion of access control training). After logging into the platform, users can independently search for virtual keys that meet their needs, submit an application, and the system automatically reviews it (verifying user eligibility according to preset rules). Once approved, the virtual key is sent to the user's device, enabling self-service retrieval. The entire process records the user's steps and timestamps, ensuring the standardization and monitorability of the retrieval process. When a user approaches the access control system using the virtual key, the access controller first reads the target version data of the virtual key, extracting key information such as ID, status, spatial range, and time range; simultaneously, it acquires current environmental data (such as time and location coordinates). The controller checks the virtual key status as "normal" according to the preset permission verification rules, whether the current time is within the allowed time period, and whether the current location is within the authorized space. If all verifications pass, it sends an opening command to the access control actuator (such as a motor or electromagnetic lock) and records a successful opening log. If any verification item fails, it refuses to open the door and records the reason for failure and time, ensuring the security and reliability of the access control system.

[0076] Specifically, virtual keys replace traditional physical keys, reducing the risk of lost or stolen keys. Dynamic access control effectively prevents unauthorized access. Permissions are generated by combining real-time requests and historical data analysis, accurately identifying abnormal behavior and improving system security. Machine learning models are used to comprehensively analyze user behavior, risk assessments, and optimization suggestions, enabling automatic permission adjustments and reducing manual intervention. Parameters are dynamically optimized based on feedback and environmental data, continuously improving the rationality of permission allocation. The number and spatial range of virtual keys are allocated on demand, avoiding resource waste. Predictive models optimize the efficiency of access control equipment, reducing operating costs.

[0077] Specifically, such as Figure 2 As shown, the process of step S1 includes:

[0078] Step S11 is used to obtain the type distribution parameters of school personnel, the spatial distribution density parameters of access control equipment, and the average daily personnel entry and exit time distribution parameters.

[0079] Specifically, school personnel are categorized into different types such as teachers, students (which can be further subdivided into undergraduates, graduate students, etc.), administrative staff, support staff, and visitors. The specific numbers of each type of personnel are obtained through the school's personnel management system and student registration management system. For example, the list and number of teachers and administrative staff are exported from the personnel management system, and the number of students of each type is counted from the student registration management system. The proportion of each type of personnel to the total number of school personnel is calculated to obtain type distribution parameters. For example, if the school has 10,000 people, including 1,000 teachers, 8,000 students (6,000 undergraduates and 2,000 graduate students), 500 administrative staff, 300 support staff, and the number of visitors can be calculated by averaging visit records over a certain period, etc. The school is divided into functional areas such as teaching areas, dormitory areas, administrative areas, library areas, gymnasium areas, and canteen areas. The number of access control devices in each area is counted. For example, the teaching area has 50 classrooms, each with one access control device, totaling 50 access control devices; the dormitory area has 10 dormitory buildings, each with two access control devices, totaling 20 access control devices. The number of access control devices per unit area in each area is calculated to obtain the spatial distribution density parameter. For example, if the teaching area is 10,000 square meters and has 50 access control devices, the density is 0.005 access control devices per square meter. The access control system records the entry and exit times of personnel over a period of time (e.g., one month or one semester). The day is divided into multiple time periods, for example, one hour per period, from 0:00 to 24:00, resulting in 24 time periods. The number of people entering and exiting in each time period is counted, and the average daily percentage of people entering and exiting in each time period is calculated to obtain the entry and exit time distribution parameter. For example, the average daily number of people entering and exiting between 8:00 and 9:00 AM accounts for 20% of the total daily number of people entering and exiting.

[0080] Step S12: Determine the initial number of virtual keys according to the type distribution parameter number, allocate corresponding spatial ranges to access control devices in different areas according to the spatial distribution density parameter to obtain the initial spatial range, and determine the initial time period range according to the entry and exit time period distribution parameter.

[0081] Specifically, step S12 includes the following process:

[0082] Step S121: Determine the initial quantity based on the type distribution parameters and the preset virtual key base number allocated to each type of personnel;

[0083] Step S122: Identify high-density areas and low-density areas based on the spatial density distribution parameters, and allocate corresponding initial spatial ranges to access control devices in different areas in combination with preset spatial allocation rules;

[0084] Step S123: Determine the initial time range based on the entry and exit time distribution parameters and the preset time allocation rules.

[0085] Specifically, based on the access needs of different types of personnel in the school for work, study, etc., a preset base number of virtual keys is allocated to each type of personnel. For example, teachers who frequently need to enter and exit teaching buildings and office buildings for teaching and office activities are preset to be allocated 5 virtual keys per teacher; students who mainly move around in teaching areas and dormitory areas are preset to be allocated 3 virtual keys per student. The obtained personnel type distribution parameters of the school are multiplied by the corresponding preset base number of virtual keys to obtain the initial number of virtual keys. For example, if the school has 1,000 teachers and 8,000 students, according to the above preset base number, the initial number of virtual keys is 1,000 × 5 + 8,000 × 3 = 29,000 keys. Based on the spatial distribution density parameters of access control devices in different areas of the school, a density threshold is set to distinguish between high-density and low-density areas. For example, a density threshold of 0.003 access control devices per square meter is set. The spatial distribution density of access control devices in each area is compared with the threshold; areas with a density higher than the threshold are high-density areas, and areas with a density lower than the threshold are low-density areas. For example, the teaching area has a density of 0.005 access control devices per square meter, which is higher than the threshold and is considered a high-density area; while the gymnasium area has a density of 0.002 access control devices per square meter, which is lower than the threshold and is considered a low-density area. High-density areas, due to the large number and concentrated distribution of access control devices, may involve multiple important or functionally complex locations. Therefore, each access control device can be assigned a smaller and more precise spatial range to achieve refined management. For example, the spatial range of the access control device at the entrance of each classroom in the teaching building can be limited to the area at the classroom entrance and inside, with a radius of approximately 2 meters. Low-density areas have relatively dispersed and fewer access control devices, which may be some entrances and exits or areas with single functions. Each access control device can be assigned a relatively larger spatial range. For example, the spatial range of the access control device at the main gate connecting the school to the outside world can be set to an area with a radius of 5 meters centered on the access control device, covering the area where people may enter and exit, including the gate and surrounding roads. Based on the above rules, corresponding spatial ranges are assigned to the access control devices in different areas to obtain the initial spatial range. Based on the average daily entry and exit time distribution parameters of school personnel, peak entry and exit times are identified, such as 7-9 AM, 11 AM-1 PM, and 5-7 PM. During peak times, with frequent personnel movement, to ensure efficiency and security, the effective time range of virtual keys can be appropriately extended, or the number of access permissions for access control devices can be increased. During periods with less personnel movement, such as 11 PM to 5 AM, virtual key permissions can be tightened, the effective time range shortened, or access to access control devices in certain areas can be restricted. Combining the above time allocation rules and entry / exit time distribution parameters, an initial time range is determined.For example, for access control equipment in teaching areas, the initial effective time range for virtual keys is set from 6:00 AM to 11:00 PM on weekdays, based on teaching schedules and peak periods for personnel entry and exit. For access control equipment in dormitory areas, considering students' daily routines, it is set to be effective 24 hours a day, but the virtual key access permissions for external personnel can be restricted during late-night hours.

[0086] Specifically, the collected parameters provide rich data support for subsequent dynamic adjustment of permissions and analysis of abnormal behavior, helping to achieve intelligent and refined access control management. Precise permission configuration reduces the cumbersome process of user application and permission adjustment, improves access efficiency, and simultaneously ensures campus security, creating a convenient and safe campus environment. Whether determining the number of virtual keys, spatial range, or time range, the principle of on-demand allocation is followed to ensure that resource investment accurately matches actual needs, avoiding resource idleness or insufficiency.

[0087] Specifically, such as Figure 3 As shown, the process of step S2 includes:

[0088] Step S21: Obtain the user's historical access records according to the initial parameters, and obtain the user's historical abnormal records according to the user's real-time request information;

[0089] Specifically, all access control records related to the user over a past period are extracted from the system database or logs, including successful and failed attempts, access time, access location (access control ID or area), and the version of the virtual key used. These records reflect the user's regular access patterns and habits. Records of access behavior flagged as abnormal by the user over a past period are also extracted from the system database or logs, such as multiple failed attempts, access at unauthorized times / areas, and records of temporary revocation or adjustment of permissions. These records reflect past risky behaviors or permission changes by the user.

[0090] Step S22: Using the initial spatial range, the initial time range, the historical access records, and the initial ID as inputs, construct a probability prediction model to predict the probability value of a user accessing each sub-region within the initial spatial range within the initial time range, and obtain the prediction result.

[0091] Specifically, a pre-trained probabilistic prediction model (e.g., a model based on time series analysis, user profiling, or collaborative filtering) is used. This model understands the user's historical behavior (historical access records from S21) and the currently set initial spatial and temporal ranges. The initial spatial range (defining the geographical boundaries of the prediction), the initial time period range (defining the time window of the prediction), the user's historical access records (used to learn user access habits), and the initial ID (used for extracting or associating user features in the model) are input into the probabilistic prediction model. After the model runs, it outputs a prediction result. This result is typically a probability distribution showing the predicted probability value of a user visiting each (or each sub) region within the initial spatial range during the initial time period. For example, the output might be a dictionary or matrix where the keys / rows are region identifiers and the values / columns are the corresponding access probabilities.

[0092] Step S23: Using the real-time request information and the historical anomaly records as input, construct a risk assessment model to evaluate the risk score of the current request information and obtain the assessment result;

[0093] Specifically, a risk assessment model is constructed, taking real-time request information and historical anomaly records as input. By analyzing information such as the user's current request access time and target area, combined with the user's past anomaly records, the risk level of the current request is assessed. Specifically, firstly, features are extracted from the real-time request information and historical anomaly records, including whether the access time is during peak hours and whether the target area is a highly sensitive area. Then, machine learning algorithms such as decision trees, support vector machines, or neural networks are used to train the extracted features to construct a risk assessment model, which is used to predict the risk score of the current request information.

[0094] Step S24: Use the historical access records, the permission change history in the historical data, and the initial parameters as input to build a suggestion model and output optimized suggestions to obtain suggestion results;

[0095] Specifically, a suggestion model is constructed, taking historical access records, permission change history, and initial parameters as input. By analyzing the user's historical access patterns and permission change occurrences, and combining information such as spatial and time ranges in the initial parameters, an optimization suggestion is provided to the user. Examples include: "Suggest expanding the access area to area X," "Suggest removing access to area Z within time period Y," and "Suggest extending the permission validity period to day D." These suggestions aim to make permissions more aligned with the user's actual needs or consistent with historical management strategies.

[0096] Step S25: Perform a comprehensive analysis based on the prediction results, the evaluation results, and the suggested results to obtain the initial permission results.

[0097] Specifically, step S25 includes the following process:

[0098] Step S251: Extract the access probability value of each sub-region based on the prediction result, and determine the intensity of user access demand in each sub-region according to the preset probability threshold. Mark the sub-region with the access probability value greater than the probability threshold as the core access region.

[0099] Specifically, the probability values ​​of a user accessing each sub-region within the initial spatial range are obtained within the initial time frame. These probability values ​​are typically presented in matrix or list form, with each sub-region corresponding to a probability value, representing the likelihood of a user accessing that sub-region. For example, the prediction results show that the probability of a user accessing sub-region A is 0.8, and the probability of accessing sub-region B is 0.4, etc. Based on campus security management strategies and actual access needs, a preset probability threshold is used to determine the intensity of a user's access demand for each sub-region. For example, setting the probability threshold to 0.6 means that sub-regions with an access probability greater than 0.6 are considered core access areas where users have a high access demand. Sub-regions with access probability values ​​greater than the preset probability threshold are marked as core access areas. For example, based on the above prediction results and threshold setting, the access probability of sub-region A is 0.8, which is greater than the threshold of 0.6, therefore sub-region A is marked as a core access area. In this way, the areas most likely to be accessed by a user within a specific time period can be clearly identified, providing a key reference for subsequent permission allocation.

[0100] Step S252: The risk scores in the assessment results are graded, and a risk threshold range is set to obtain the risk judgment result, wherein...

[0101] If the risk score is below the first risk threshold, it is determined to be a low-risk request; if the risk score is greater than or equal to the first risk threshold and less than the second risk threshold, it is determined to be a medium-risk request; if the risk score is greater than the second risk threshold, it is determined to be a high-risk request.

[0102] Specifically, risk threshold ranges are set to classify risk levels. These thresholds are typically determined based on historical data, the performance of risk assessment models, and campus security policies. For example, a first risk threshold of 0.3 and a second risk threshold of 0.6 might be set. This means that a risk score below 0.3 is considered a low-risk request; a score greater than or equal to 0.3 and less than 0.6 is considered a medium-risk request; and a score greater than 0.6 is considered a high-risk request. It is important to note that the thresholds should be set after thorough risk analysis and verification to ensure effective differentiation between requests of different risk levels. The risk assessment result is determined based on the range of the risk score. For example, a request with a risk score of 0.2 is considered a low-risk request; a score of 0.5 is considered a medium-risk request; and a score of 0.7 is considered a high-risk request. Different risk levels will correspond to different permission allocation strategies; for example, high-risk requests may require stricter approval processes or restricted access.

[0103] Step S253: Convert the optimization suggestions in the suggested results into parameter adjustment instructions;

[0104] Specifically, optimization suggestions might include increasing or decreasing access permissions to certain areas, adjusting access time ranges, or raising or lowering permission levels. For example, a suggestion model might recommend increasing a user's access permissions to a specific area of ​​the library, or extending a user's access time in a certain teaching building. These optimization suggestions need to be translated into specific parameter adjustment instructions. This requires clearly defining the correspondence and adjustment rules for various permission parameters in the system. For example, a suggestion to increase access permissions translates to adding the corresponding area's permission parameters to the target version of the virtual key; a suggestion to adjust access time translates to instructions to modify the time range parameter. These instructions should be presented in a format that the system can recognize and execute, ensuring that the optimization suggestions are accurately implemented in the permission configuration.

[0105] Step S254: Generate an initial permission result based on the core access area, the risk assessment result, and the parameter adjustment instruction.

[0106] Specifically, the core access area reflects a user's normal access needs, the risk assessment result reflects the security of the request, and the parameter adjustment instruction provides optimization direction. For example, if a request's core access area is Area A of the teaching building, the risk assessment result is low risk, and the parameter adjustment instruction suggests increasing access permissions to that area, then during the comprehensive analysis, the user will be more likely to be granted greater access permissions. In the comprehensive analysis process, different factors can be assigned weights to highlight their importance in permission decisions. For example, the weight of the core access area can be set to 0.4, the weight of the risk assessment result to 0.3, and the weight of the parameter adjustment instruction to 0.3. Based on the weights and specific manifestations of different factors, weighted calculations or logical judgments are performed to ultimately determine the user's initial permission result. For example, for the aforementioned low-risk request, where both the core access area and the parameter adjustment instruction support increasing permissions, after weighted calculation, it is decided to grant the user full access permissions to Area A of the teaching building; while for a high-risk request, even if there is a high demand for the core access area, access permissions may be restricted or further approval may be required. Based on the results of the comprehensive analysis, the user's initial permission result is generated. The initial permission results should clearly define the user's access permissions in each sub-region, including the allowed area range, access time range, and permission level.

[0107] Specifically, by extracting access probability values ​​and marking core access areas, the system can accurately grasp the user's main activity range, providing strong support for permission configuration in key areas while avoiding over-allocation of permissions and improving the granularity of permission management. Risk scores are graded, enabling the system to adopt differentiated permission control strategies based on different risk levels. Optimization suggestions are translated into specific parameter adjustment instructions, enhancing the executability of the suggestions and ensuring that optimization measures are accurately implemented in permission configuration. This allows for timely improvement and optimization of permission management strategies to adapt to changes in the campus environment and user needs. By comprehensively considering core access areas, risk assessment results, and parameter adjustment instructions, the system effectively balances user needs and security management. While meeting users' reasonable access needs, it effectively controls risks, resulting in more reasonable and reliable initial permission results, providing strong support for the stable operation of the campus access control system.

[0108] Specifically, such as Figure 4 As shown, the process of step S3 includes:

[0109] Step S31: Collect feedback information related to the initial permission result. The feedback information includes the user's experience with the virtual key permission, the ease of permission application, and the rationality of permission allocation.

[0110] Specifically, user feedback is collected extensively through various means, including online questionnaires, feedback modules within access control systems, campus forums, emails, and offline suggestion boxes, making it convenient for different user groups to provide feedback. Feedback requests are proactively sent to users at fixed time intervals (such as monthly or quarterly) to improve the comprehensiveness and timeliness of feedback information.

[0111] Step S32: Collect environmental data, including changes in personnel flow in the area where the access control device is located, distribution of access time, device operating status, and security incident records;

[0112] Specifically, this involves installing infrared thermal sensors, video surveillance systems, or facial recognition data recording devices for access control to monitor the flow of people in the area in real time and to track the number of people entering and exiting at different times and in different areas. The access control system's backend automatically records the access time of all users, creating a data record of access time distribution. Analyzing this data reveals the distribution of peak and off-peak periods. A device status monitoring module is deployed to collect real-time operational data from the access control devices, such as online time, number of power outages, and network connection stability. It also records the regular maintenance and repair status of the devices. A security incident reporting system is established to ensure that all security incidents (such as unauthorized intrusions and abuse of privileges) are recorded with detailed information by on-site security personnel or the system's automatic detection mechanism, including the time, location, and handling measures taken.

[0113] Step S33: Analyze the feedback information and the environmental data to determine whether the initial parameters need to be adjusted. If adjustment is required, adjust at least one parameter in the initial parameters according to the preset parameter adjustment rules to obtain the adjustment result.

[0114] Specifically, step S33 includes the following process:

[0115] Step S331: Quantitatively analyze the feedback information, set a threshold for user experience satisfaction, and adjust the initial parameters when the proportion of negative evaluations in the feedback information exceeds the threshold.

[0116] Step S332: Dynamically monitor the environmental data, set abnormal thresholds for personnel flow, access time, and security events, and adjust the initial parameters when any indicator is detected to exceed the abnormal threshold.

[0117] Step S333: According to the preset parameter adjustment rules, at least one parameter among the initial parameters is adjusted separately or in combination for different types of feedback information and abnormal environmental data situations.

[0118] Specifically, the collected feedback information is categorized and organized to establish a quantitative indicator system. For example, user feedback on virtual key access, the ease of access application, and the rationality of access allocation are quantified into different indicators. Based on campus management goals and historical user satisfaction survey data, thresholds for user experience satisfaction are set. For example, a satisfaction rate below 60% is set as the dissatisfaction threshold. Quantitative scores for each feedback indicator are calculated, and when the proportion of negative reviews exceeds the set threshold, an initial parameter adjustment process is triggered. Personnel flow changes are monitored in real time using personnel flow sensors or video surveillance systems installed in access control areas. Abnormal thresholds for personnel flow are set; for example, a flow rate exceeding 1000 people per hour in a certain area is considered abnormal, potentially indicating increased access demand and requiring adjustment of access permission configurations. Access time data recorded by the access control system is used to analyze access time distribution. Abnormal thresholds for access time are set; for example, an access request exceeding a certain number (e.g., more than 50 times per hour) in a certain area outside of working hours is considered abnormal, potentially requiring adjustment of access time permissions for that area. A security incident monitoring system is established to collect security incident records in real time. Set anomaly thresholds for security incidents. For example, setting more than three security incidents per month in a certain area as abnormal indicates potential security vulnerabilities in the area's permission configuration, requiring adjustment of initial parameters. Develop corresponding single-factor adjustment rules for different types of feedback or abnormal environmental data. For instance, when feedback indicates that the difficulty of permission application is below the threshold, adjust parameters related to the permission application process, simplify the application steps, or add application guidelines. When multiple types of feedback or abnormal environmental data occur simultaneously, develop combined adjustment rules. For example, when feedback indicates user dissatisfaction with the reasonableness of permission allocation and environmental data detects abnormal personnel flow, it may be necessary to adjust both the spatial range and access time range parameters of the virtual key simultaneously.

[0119] Specifically, by quantifying and analyzing user feedback and setting clear satisfaction thresholds, the decision-making process becomes more objective, avoiding biases from subjective judgments and ensuring that necessary adjustments are only made when user satisfaction significantly declines. Through dynamic monitoring of environmental data and setting anomaly thresholds, the system can identify potential safety risks and operational problems, adjusting parameters in a timely manner to prevent further deterioration and ensure campus safety. Based on preset parameter adjustment rules, the system can flexibly adjust single or combined parameters according to different types of feedback and abnormal environmental data, ensuring precise and effective adjustments and avoiding over- or under-adjustment.

[0120] Specifically, step S4 includes the following process:

[0121] Step S41: Map and match the adjustment result with the initial permission result to identify the permission items that need to be adjusted to obtain the identification result;

[0122] Specifically, the adjusted permissions are compared in detail with the initial permissions to identify the permissions that need adjustment. For example, if the adjustment results indicate that access time for a certain area needs to be extended, then the access time permission for that area is identified as needing adjustment. Based on the comparison results, all permissions that need adjustment are listed, including their specific values ​​in the initial permissions and their target values ​​in the adjusted results. For example, if the initial permissions show access time for a certain area as 8:00-18:00, and the adjustment requires changing it to 7:00-19:00, then this access time permission is identified as needing adjustment.

[0123] Step S42: Modify the recognition result according to the adjustment result to obtain the modified result;

[0124] Specifically, step S42 includes the following process:

[0125] Step S421: Locate the corresponding permission item in the recognition result according to the parameter modification instruction specified in the adjustment result;

[0126] Specifically, the analysis involves analyzing the parameter modification instruction format in the adjustment results to clarify the information type and structure contained in the instructions, such as permission item identifiers, modification types (update or calculation), and modification values ​​or rules. The permission item identifiers to be adjusted are extracted from the modification instructions; these identifiers are used to accurately locate the corresponding permission items in the initial permission results. For example, the permission item identifier could be a sub-region ID, access time period code, etc. A mapping relationship is established between the parameter modification instructions and the permission items in the initial permission results. The corresponding permission item is then searched for in the data structure (such as a list, dictionary, etc.) of the initial permission results using the permission item identifier. Based on the extracted permission item identifier, the specific permission item is retrieved and located in the initial permission results. For example, the permission item matching a given sub-region ID is searched in the permission item list.

[0127] Step S422: Update the specific parameter values ​​of the permission items located in the identification results according to the modification values ​​or modification rules in the parameter modification instructions; or, calculate them.

[0128] Specifically, if the modification command specifies a particular value, the current value of the located permission item is directly replaced with the new modified value. For example, changing the access permission of a sub-area from "read-only" to "read-write". If the modification command provides a modification rule, the current value of the permission item is calculated according to the rule to obtain a new parameter value. For example, if the rule is "extend the access time by 3 minutes", then a new end time needs to be calculated.

[0129] Step S423: Verify whether the modified permission item conforms to the preset permission rules and format requirements;

[0130] Specifically, verify whether the modified permission items conform to the preset permission rules, such as access time not exceeding the maximum allowed range by the system, and the access range must be an area within the campus. Check whether the modified permission items meet the data format requirements, such as whether the time format is correct and whether the area ID exists.

[0131] Consistency verification: Ensure the consistency between modified permission items and other related permission items, such as whether the permission relationship between parent and child regions is reasonable.

[0132] Step S424: The modified permission item that has passed verification is determined as the modification result.

[0133] Specifically, the verified modified permission items are recorded to form the modification result. The modification result should include information such as the identifier of the permission item and its modified value. In the target version of the virtual key, the information of the relevant permission items is updated to ensure that the target version reflects the latest modification result.

[0134] Step S43: Combine the modified result with the unadjusted permission items to generate the target version of the virtual key.

[0135] Specifically, based on the initial permission results, those permission items not marked as needing adjustment in step S41 are identified. These permission items remain in their original state. The modified result generated in step S42 (i.e., the updated set of permission items) is merged with the set of unadjusted permission items (initial parameters) identified in step 1. During the merging process, redundancy (e.g., two identical permissions for the same access control) or conflicts (e.g., permissions that both allow and deny access control) are checked for and cleaned up or resolved according to preset rules (usually retaining more lenient or up-to-date permissions). The final merged and cleaned set of permission items is combined with other basic attributes of the virtual key (such as ID, name, status, etc., which may be determined in step S1 or subsequent steps) to form a complete target version of the virtual key. This target version contains all the latest, adjusted permission information.

[0136] Specifically, by mapping and matching the adjustment results with the initial permission results, the system accurately identifies the permission items that need adjustment, ensuring the targeted nature and effectiveness of the adjustment operations. The modified permission items are organically combined with the unadjusted permission items to form a complete virtual key target version, guaranteeing the comprehensiveness and accuracy of permission configuration. It can quickly locate the permission items that need adjustment, improving adjustment efficiency and shortening response time. It flexibly executes parameter value updates or calculations based on modification instructions, adapting to diverse adjustment needs and enhancing the system's flexibility and adaptability. Through accurate and timely permission adjustments, it ensures that users obtain reasonable access permissions, improving user experience and satisfaction.

[0137] On the other hand, the present invention provides an access control system based on virtual key management, characterized in that it includes:

[0138] The attribute definition module is used to obtain the initial attributes of the virtual key to obtain initial parameters, including initial ID, initial name, initial status, initial validity period, initial spatial range, and initial time period range. It is also used to obtain the initial number of virtual keys, the user's historical data, and the user's real-time request information.

[0139] The version generation module is connected to the attribute definition module. It generates an initial version of the virtual key based on the initial parameters and performs calculations based on a pre-trained machine learning model to obtain the initial permission result.

[0140] A data collection module, connected to the version generation module, is used to collect feedback information related to the initial permission result, or to adjust at least one parameter in the initial parameters based on environmental data to obtain an adjustment result.

[0141] A parameter adjustment module, connected to the data collection module, adjusts the initial permission result according to the adjustment result to generate a target version of the virtual key;

[0142] The permission verification module is connected to the parameter adjustment module, which assigns the target version to the user, or sets it to be claimed by the user independently, and performs permission verification based on the user and the target version.

[0143] Specifically, the access control access key management method based on virtual key management provided by the present invention can execute the access control access key management system based on virtual key management in the embodiments of the present invention, and can achieve the same technical effect, which will not be described in detail here.

[0144] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0145] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for managing access authority based on virtual key management, characterized by, The method comprises the following steps: Step S1, obtaining initial attributes of a virtual key to obtain initial parameters, the initial parameters comprising an initial ID, an initial name, an initial state, an initial validity period, an initial space range, and an initial time range, and obtaining an initial number of virtual keys, historical data of a user, and real-time request information of the user; Step S2, generating an initial version of the virtual key according to the initial parameters, and performing calculation based on a pre-trained machine learning model to obtain an initial permission result; The process of step S2 comprises: Step S21, obtaining historical access records corresponding to the user according to the initial parameters, and obtaining historical abnormal records of the user according to the real-time request information of the user; Step S22, constructing a probability prediction model by taking the initial space range, the initial time range, the historical access records, and the initial ID as inputs to predict probability values of the user accessing each sub-region in the initial space range within the initial time range to obtain a prediction result; Step S23, constructing a risk assessment model by taking the real-time request information and the historical abnormal records as inputs to assess a risk score of the current request information to obtain an assessment result; Step S24, constructing a suggestion model by taking the historical access records, permission change history in the historical data, and the initial parameters as inputs to output an optimization suggestion to obtain a suggestion result; Step S25, performing comprehensive analysis according to the prediction result, the assessment result, and the suggestion result to obtain the initial permission result; Step S3, collecting feedback information related to the initial permission result, or adjusting at least one parameter in the initial parameters based on environmental data to obtain an adjustment result; Step S4, adjusting the initial permission result according to the adjustment result to generate a target version of the virtual key; Step S5, assigning the target version to the user, or setting the target version for the user to independently collect, and performing permission verification according to the user and the target version. 2.The virtual key management-based access authority management method of claim 1, wherein The process of step S1 comprises: Step S11, obtaining a type distribution parameter of school personnel, a space distribution density parameter of access control equipment, and an average daily personnel access time range distribution parameter; Step S12, determining an initial number of virtual keys according to the type distribution parameter, assigning corresponding space ranges to access control equipment in different regions according to the space distribution density parameter to obtain the initial space range, and determining an initial time range according to the access time range distribution parameter. 3.The virtual key management-based access authority management method according to claim 2, characterized in that, The process of step S12 comprises: Step S121, determining the initial number according to the type distribution parameter and a preset virtual key base number corresponding to each type of personnel; Step S122, identifying high-density regions and low-density regions according to the space distribution density parameter, and assigning corresponding initial space ranges to access control equipment in different regions in combination with a preset space allocation rule; Step S123, determining the initial time range in combination with a preset time allocation rule according to the access time range distribution parameter. 4.The virtual key management-based access authority management method according to claim 3, characterized in that, The process of step S25 comprises: Step S251, extracting the access probability value of each sub-region according to the prediction result, and judging the access demand intensity of the user in each sub-region according to a preset probability threshold value, and marking the sub-region with the access probability value greater than the probability threshold value as a core access region; Step S252, grading the risk score in the evaluation result, setting a risk threshold interval to obtain a risk judgment result, wherein, if the risk score is lower than a first risk threshold, it is determined as a low-risk request; if the risk score is greater than or equal to the first risk threshold and less than a second risk threshold, it is determined as a medium-risk request; if the risk score is greater than the second risk threshold, it is determined as a high-risk request; Step S253, converting the optimization suggestion in the suggestion result into a parameter adjustment instruction; Step S254, comprehensively generating an initial permission result according to the core access region, the risk judgment result and the parameter adjustment instruction. 5.The virtual key management-based access authority management method according to claim 4, characterized in that, The process of step S3 includes: Step S31, collecting feedback information related to the initial permission result, the feedback information including user experience of virtual key permission, difficulty of permission application and rationality of permission allocation; Step S32, collecting environment data, the environment data including personnel flow change, access time distribution, device running state and security event record of the area where the access control device is located; Step S33, analyzing the feedback information and the environment data to determine whether the initial parameters need to be adjusted, and if so, adjusting at least one parameter in the initial parameters according to a preset parameter adjustment rule to obtain the adjustment result. 6.The virtual key management-based access authority management method according to claim 5, characterized in that, The process of step S33 includes: Step S331, quantitatively analyzing the feedback information, and setting a threshold value of user experience satisfaction, when the proportion of negative evaluation in the feedback information exceeds the threshold value, adjusting the initial parameters; Step S332, dynamically monitoring the environment data, and setting abnormal threshold values of personnel flow, access time and security event, when any index exceeds the abnormal threshold value, adjusting the initial parameters; Step S333, according to a preset parameter adjustment rule, adjusting at least one parameter in the initial parameters respectively, or in combination, for different feedback information types and environment data abnormal situations. 7.The virtual key management-based access authority management method of claim 6, wherein, The process of step S4 includes: Step S41, mapping and matching the adjustment result with the initial permission result to identify the permission items that need to be adjusted to obtain an identification result; Step S42, modifying the identification result according to the adjustment result to obtain a modified result; Step S43, combining the modified result with the unadjusted permission items to generate a target version of the virtual key. 8.The virtual key management-based access authority management method of claim 7, wherein, The process of step S42 includes: Step S421, locating the corresponding permission item in the identification result according to the parameter modification instruction specified in the adjustment result; Step S422, according to the modification value or modification rule in the parameter modification instruction, updating or calculating the specific parameter value of the located permission item in the identification result. Step S423: verifying whether the modified permission item meets preset permission rules and format requirements; Step S424: determining the modified permission item that passes the verification as the modification result.

9. A virtual key management-based access authority management system based on the virtual key management-based access authority management method according to any one of claims 1 to 8, characterized by Comprise: An attribute definition module is configured to obtain initial attributes of a virtual key to obtain initial parameters, the initial parameters including an initial ID, an initial name, an initial state, an initial validity period, an initial space range, and an initial time range, and is further configured to obtain an initial number of virtual keys, historical data of a user, and real-time request information of the user; A version generation module, connected with the attribute definition module, is configured to generate an initial version of the virtual key according to the initial parameters and perform calculation based on a pre-trained machine learning model to obtain an initial permission result; A data collection module, connected with the version generation module, is configured to collect feedback information related to the initial permission result or adjust at least one parameter in the initial parameters based on environmental data to obtain an adjustment result; A parameter adjustment module, connected with the data collection module, is configured to adjust the initial permission result according to the adjustment result to generate a target version of the virtual key; A permission verification module, connected with the parameter adjustment module, is configured to assign the target version to the user or set the target version for the user to independently collect, and perform permission verification according to the user and the target version.

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