Access control authority management method and system based on virtual key management

Abstract

The invention relates to the technical field of computers, in particular to an access control authority management method and system based on virtual key management, and the method comprises the steps: firstly, obtaining an initial attribute of a virtual key, user historical data and a real-time request, and forming an initial parameter; then, generating an initial version of the virtual key by using the parameters, and calculating an initial authority through a pre-trained machine learning model; then, the system collects feedback about the initial authority, or adjusts the initial parameter according to the environment data to obtain an adjustment result; on the basis of the adjustment result, the initial permission is optimized, and a target version of the virtual key is generated; and finally, distributing the target version to the user or allowing the user to autonomously get the target version, and when the user tries to access, performing permission verification according to the identity of the user and the target version. According to the invention, dynamic, intelligent and flexible access control authority management is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, in particular to a door access permission management method and system based on virtual key management. BACKGROUND

[0002] In today's campus management, the entrances of classrooms, offices, dormitories, etc. are installed with intelligent access control devices, including intelligent door locks, intelligent door magnets, etc., for managing personnel access. With more and more intelligent devices, in order to improve the overall management efficiency, a door access control system is also built to uniformly manage the intelligent access control devices of the whole school and to perform batch personnel authorization management, etc.

[0003] With the introduction of the access control system, the door access management tends to evolve into a more refined management mode. In the access control system, the following dimensions are managed: user dimension: people who can open doors are added to the system; place dimension: all intelligent access control devices are added to the system; time dimension: time range for opening doors is set;

[0004] In combination with the above information, in traditional access control / door lock devices or management systems, whether a person can open an access control device is usually realized by using access control permissions, that is, assigning a person with a use permission of an access control device. In combination with some time settings, a person can open the door of a space at a certain time. In a school scenario, this person-based permission management mode has the following difficulties: there are a large number of personnel in the school, some universities have tens of thousands of people; the types of personnel in the school are also very complex, including faculty, logistics, students, administrators, etc.; there are a large number of access control devices in the school, hundreds of classrooms or function rooms, etc.; it is necessary to refine each day granularity, and some time periods of each day can open the door;

[0005] In view of the above four dimensions, it will become very complex to manage the access control permissions in a system, and it is very inconvenient to manage. Especially in some scenarios of frequently performing dynamic authorization, performing batch permission adjustment, temporarily canceling / increasing authorization, etc., a lot of time will be spent to find the access control devices that need to be modified. There is a need for a more convenient and fast method and system to realize batch permission management and quickly perform dynamic permission adjustment to manage the authorization process of intelligent access control devices. SUMMARY

[0006] Therefore, the present application provides a door access permission management method and system based on virtual key management to solve the foregoing problems in the prior art.

[0007] To achieve the above object, the application provides a door access permission management method based on virtual key management, comprising:

[0008] Step S1, used to obtain initial attributes defining a virtual key to obtain initial parameters, the initial parameters including initial ID, initial name, initial state, initial validity period, initial space range and initial time range, and used to obtain initial quantity of virtual keys, historical data of users and real-time request information of users;

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

[0010] Step S3, used 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;

[0011] Step S4, adjusting the initial permission result according to the adjustment result to generate a target version of the virtual key;

[0012] Step S5, assigning the target version to the user, or setting it for the user to take it by himself / herself, and performing permission verification according to the user and the target version.

[0013] Further, the process of step S1 comprises:

[0014] Step S11, used to obtain type distribution parameters of school personnel, space distribution density parameters of access control devices and average daily personnel access time period distribution parameters;

[0015] Step S12, determining the initial quantity of virtual keys according to the type distribution parameters, assigning corresponding space ranges to access control devices in different regions to obtain the initial space range according to the space distribution density parameters, and determining the initial time range according to the access time period distribution parameters.

[0016] Further, the process of step S12 comprises:

[0017] Step S121, determining the initial quantity according to the type distribution parameters and the preset virtual key base corresponding to each type of personnel;

[0018] Step S122, identifying high-density and low-density regions according to the space density distribution parameters, and assigning corresponding initial space ranges to access control devices in different regions in combination with a preset space allocation rule;

[0019] Step S123, determining the initial time range according to the access time period distribution parameters in combination with a preset time allocation rule.

[0020] Further, the process of step S2 comprises:

[0021] Step S21, obtaining the historical access record corresponding to the user according to the initial parameters, and obtaining the historical abnormal record of the user according to the real-time request information of the user;

[0022] Step S22, constructing a probability prediction model by taking the initial space range, the initial time range, the historical access record and the initial ID as inputs to predict the probability value of the user accessing each sub-region in the initial space range within the initial time range to obtain a prediction result;

[0023] Step S23, constructing a risk assessment model by taking the real-time request information and the historical abnormal record as inputs to assess the risk score of the current request information to obtain an assessment result;

[0024] Step S24, constructing a suggestion model by taking the historical access record, the permission change history in the historical data and the initial parameters as inputs to output an optimization suggestion to obtain a suggestion result;

[0025] Step S25, performing comprehensive analysis according to the prediction result, the assessment result and the suggestion result to obtain the initial permission result.

[0026] Further, the process of step S25 comprises:

[0027] 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, and marking the sub-region with the access probability value greater than the probability threshold as a core access region;

[0028] Step S252, grading the risk score in the assessment result, and setting a risk threshold interval to obtain a risk judgment result, wherein,

[0029] If the risk score is lower than the 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 the 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;

[0030] Step S253, converting the optimization suggestion in the suggestion result into a parameter adjustment instruction;

[0031] Step S254, generating an initial permission result according to the core access region, the risk judgment result and the parameter adjustment instruction.

[0032] Further, the process of step S3 comprises:

[0033] 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;

[0034] 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;

[0035] 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.

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

[0037] Step S331, quantitatively analyzing the feedback information, setting a threshold of user experience satisfaction, and when the proportion of negative evaluation in the feedback information exceeds the threshold, adjusting the initial parameters;

[0038] Step S332, dynamically monitoring the environment data, setting abnormal threshold of personnel flow, access time and security event, and when any index exceeds the abnormal threshold, adjusting the initial parameters;

[0039] Step S333, according to the preset parameter adjustment rule, adjusting at least one parameter in the initial parameters for different feedback information types and environment data abnormal situations, respectively, or in combination.

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

[0041] Step S41, mapping and matching the adjustment result and the initial permission result to identify the permission item that needs to be adjusted to obtain an identification result;

[0042] Step S42, modifying the identification result according to the adjustment result to obtain a modified result;

[0043] Step S43, combining the modified result with the unadjusted permission item to generate a target version of the virtual key.

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

[0045] Step S421, according to the parameter modification instruction specified in the adjustment result, locating the corresponding permission item in the identification result;

[0046] Step S422, according to the modification value or modification rule in the parameter modification instruction, the specific parameter value of the permission item positioned in the identification result is updated, or calculated;

[0047] Step S423, verifying whether the modified permission item meets the preset permission rule and format requirement;

[0048] Step S424, determining the modified permission item that passes the verification as the modification result.

[0049] On the other hand, the application provides a virtual key management-based access control permission management system, characterized in that it comprises:

[0050] 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;

[0051] A version generation module is connected to the attribute definition module, 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;

[0052] A data collection module is connected to the version generation module, 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;

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

[0054] A permission verification module is connected to the parameter adjustment module, configured to assign the target version to a user, or set the target version for the user to take independently, and perform permission verification according to the user and the target version.

[0055] Compared with the prior art, the application has the beneficial effects that the application replaces traditional physical keys with virtual keys, reduces the risk of key loss or theft, effectively prevents unauthorized access through dynamic permission management, generates permissions based on real-time requests and historical data analysis, accurately identifies abnormal behavior, and improves system security level. Machine learning models are used to analyze user behavior, risk assessment, and optimization suggestions, to realize automatic adjustment of permissions and reduce manual intervention. Based on feedback and environmental data, parameters are dynamically optimized to continuously improve the rationality of permission allocation. The number of virtual keys and the space range are allocated on demand to avoid resource waste. The use efficiency of access control equipment is optimized through a prediction model to reduce operating costs.

[0056] In particular, the collected parameters provide rich data support for subsequent dynamic adjustment of permissions, analysis of abnormal behavior, and other purposes, 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 ensures campus safety, creating a convenient and safe campus environment. The determination of the number of virtual keys, spatial range, and time range follows the principle of on-demand allocation, ensuring precise matching of resource investment and actual demand, and avoiding resource idleness or deficiency.

[0057] In particular, by extracting access probability values and marking core access areas, the system can accurately grasp the main activity range of users, providing strong support for permission configuration in key areas, while avoiding excessive allocation of permissions and improving the refinement of permission management. Risk scores are processed in stages, allowing the system to adopt differentiated permission control strategies based on different risk levels. Converting optimization suggestions into specific parameter adjustment instructions enhances the executability of the suggestions, ensuring that optimization measures can be accurately implemented in permission configuration, improving and optimizing permission management strategies in a timely manner to adapt to changes in the campus environment and user needs. By considering core access areas, risk assessment results, and parameter adjustment instructions, the system fully balances the relationship between user needs and security management. While meeting users' reasonable access needs, it effectively controls risks, generating more reasonable and reliable initial permission results, providing a strong guarantee for the stable operation of the campus access control system.

[0058] In particular, by quantitatively analyzing user feedback information and setting clear satisfaction thresholds, the decision-making process becomes more objective, avoiding subjective judgment biases and ensuring that necessary adjustments are made only when user satisfaction significantly decreases. Through dynamic monitoring of environmental data and setting of abnormal thresholds, the system can identify potential security risks and operational problems, and adjust parameters in a timely manner to prevent further deterioration, ensuring campus safety. According to pre-set parameter adjustment rules, the system can flexibly adjust single or combined parameters for different types of feedback information and environmental data anomalies, ensuring that adjustment measures are precise and effective, and avoiding excessive or insufficient adjustments.

[0059] In particular, by mapping and matching the adjustment results with the initial permission results, the system accurately identifies the permissions that need to be adjusted, ensuring the relevance and effectiveness of the adjustment operations. The modified permissions are organically combined with the unadjusted permissions to form a complete virtual key target version, ensuring the completeness and accuracy of the permission configuration. The system can quickly locate the permissions that need to be adjusted, improving adjustment efficiency and shortening response time. According to the modification instructions, the system can flexibly perform parameter value updates or calculations to adapt to various adjustment needs, improving the system's flexibility and adaptability. Through accurate and timely permission adjustment, the system ensures that users have reasonable access permissions, improving user experience and satisfaction. BRIEF DESCRIPTION OF DRAWINGS

[0060] Figure 1 A flow chart of the access control authority management method based on virtual key management provided by the present invention;

[0061] Figure 2 A flow chart of step S1 in the access control authority management method based on virtual key management provided by the present invention;

[0062] Figure 3 A flow chart of step S2 in the access control authority management method based on virtual key management provided by the present invention;

[0063] Figure 4 This is a structural diagram of the access control authority management system based on virtual key management provided by the present invention. DETAILED DESCRIPTION

[0064] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0065] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain 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 the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating 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 does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0067] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0068] See also Figure 1 As shown, the present invention provides an access control authority management method based on virtual key management, comprising:

[0069] Step S1, obtaining initial attributes defining the virtual key to obtain initial parameters, including initial ID, initial name, initial state, initial validity period, initial spatial range and initial time period range, and obtaining initial number of virtual keys, historical data of the user and real-time request information of the user;

[0070] Specifically, the initial ID assigns a unique identifier to each virtual key, which can be automatically generated randomly by the system or generated according to a specific coding rule (such as combined with user information, date, etc.), to ensure that different virtual keys can be accurately distinguished in the system. The initial name is named according to the information of the access control position, use scenario or user group associated with the virtual key, such as "office area - Zhang San's exclusive key", which is convenient for users to identify and manage. The initial state is set to "not enabled", "disabled" or "normal", which is determined according to the default policy of the access control system or the pre-configuration of the administrator. If the system is just deployed, the initial state of most virtual keys is usually "not enabled", and it is enabled according to the needs after allocation. The historical data of the user is obtained to query the past access records of the user (or user group), including access time, place, frequency, reason for rejection, etc. The type, range and duration of the virtual key permission granted to the user in the past are queried, and the historical data of the user is analyzed to identify the access mode (such as frequently accessed areas, time periods). The specific content of the access control permission request proposed by the user is obtained, such as the area to be accessed, the expected time period, the access purpose, etc. The context information related to the request is obtained, such as the time when the request is initiated, the urgency of the request, the type of device initiating the request, etc.

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

[0072] 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;

[0073] Step S4, adjusting the initial permission result according to the adjustment result to generate a target version of the virtual key;

[0074] Step S5, assigning the target version to the user, or setting it for the user to take it independently, and performing permission verification according to the user and the target version.

[0075] Specifically, the administrator selects appropriate virtual keys from the target version library according to the user's application information, department needs or established permission allocation strategy in the access control management system background, and sends them to the user's mobile device (such as a mobile phone, a smart card, etc.) through the system. After receiving the virtual keys, the user automatically installs or activates the virtual key application, completing the allocation process. During the allocation process, the allocation operation log is recorded, including allocation time, allocation object, virtual key ID, etc. information, which is convenient for subsequent tracing and management. On the user self-service platform of the access control system, the target version information of the virtual keys that can be obtained is published, and the obtaining conditions (such as identity authentication, completion of access control training, etc.) are clearly stated. After the user logs in to the platform, the user can independently query the virtual keys that meet their own needs, submit an application for obtaining, and the system will automatically review (check the user's qualifications according to the preset rules) and send the virtual keys to the user's device after passing the review, realizing self-obtaining. The entire process records the user's operation steps and time stamps, ensuring the standardization and monitorability of the obtaining process. When the user uses the virtual key to approach the access control, the access controller first reads the target version data of the virtual key, extracts the ID, state, space range, time range, etc. key information; at the same time, it obtains the current environmental data (such as time, location coordinates, etc.). The controller verifies the state of the virtual key according to the preset permission verification rules, whether the current time is within the allowed time range, and whether the current location belongs to the authorized space range; if all the verification items pass, the controller sends an opening instruction to the access control execution mechanism (such as a motor, an electromagnetic lock, etc.), records the opening success log; if any verification item fails, the controller refuses to open the door and records the failure reason and time, etc. information, ensuring the safety and reliability of the access control system.

[0076] Specifically, virtual keys are used to replace traditional physical keys, reducing the risk of key loss or theft, and effectively preventing unauthorized access through dynamic permission management. Real-time requests and historical data analysis are combined to generate permissions, accurately identify abnormal behavior, and improve system security level. Machine learning models are used to analyze user behavior, risk assessment and optimization suggestions, enabling automatic adjustment of permissions and reducing manual intervention. Based on feedback and environmental data, parameters are dynamically optimized to continuously improve the rationality of permission allocation. The number of virtual keys and the space range are allocated on demand to avoid resource waste. Through a prediction model, the efficiency of access control devices is optimized to reduce operating costs.

[0077] Specifically, as shown in Figure 2 The process of step S1 includes:

[0078] Step S11 is configured to obtain type distribution parameters of school personnel, spatial distribution density parameters of access control devices, and average daily personnel access time period distribution parameters.

[0079] Specifically, the school staff is divided into teachers, students (which can be further subdivided, such as undergraduates, postgraduates, etc.), administrative staff, logistics staff, visitors, and other types. The specific number of each type of personnel is obtained through the school's personnel management system, student status management system, etc. 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 status management system. The proportion of each type of personnel in the total number of personnel in the school is calculated to obtain the type distribution parameter. For example, a school has a total of 10,000 people, including 1,000 teachers, 8,000 students (6,000 undergraduates and 2,000 postgraduates), 500 administrative staff, 300 logistics staff, and the number of visitors can be averaged by recording the number of visits within a certain period of time. The school is divided into teaching areas, dormitory areas, administrative areas, library areas, gymnasium areas, and canteen areas according to functional areas. The number of access control devices in each area is counted. For example, the teaching area has 50 classrooms, each with an access control device, for a total of 50 access control devices; the dormitory area has 10 dormitory buildings, each with 2 access control devices, for a total of 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, the teaching area has an area of 10,000 square meters, with 50 access control devices, for a density of 0.005 access control devices per square meter. The access time data of personnel within a period of time (such as a month or a semester) is recorded through the access control system. A day is divided into multiple time periods, for example, 1 hour per period, from 0 to 24 hours, divided into 24 periods. The number of personnel entering and leaving each period is counted, and the average number of personnel entering and leaving each period per day is calculated to obtain the entry and exit time period distribution parameter. For example, the average number of personnel entering and leaving the 8-9 am period is 20% of the total number of personnel entering and leaving the entire day.

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

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

[0082] Step S121, determining the initial number according to the type distribution parameter and the preset virtual key base corresponding to each type of personnel;

[0083] Step S122, identifying high-density areas and low-density areas according to the spatial density distribution parameter, and assigning corresponding initial spatial ranges to access control devices in different areas in combination with a preset spatial allocation rule;

[0084] Step S123, determining the initial time range according to the entry and exit time period distribution parameter in combination with a preset time allocation rule.

[0085] Specifically, according to the pass requirements of different types of personnel in the school, such as work and study, the preset virtual key base corresponding to the distribution of each type of personnel is allocated. For example, teachers need to frequently enter and exit teaching buildings, office buildings and other areas due to teaching, office activities, etc. Each teacher is allocated 5 virtual keys; students mainly move in the teaching area and dormitory area, and each student is allocated 3 virtual keys. The school personnel type distribution parameters obtained are multiplied by the corresponding preset virtual key base to obtain the initial number of virtual keys. For example, there are 1000 teachers and 8000 students in the school, and according to the above-mentioned preset base, the initial number of virtual keys is 1000*5+8000*3=29000. According to the space distribution density parameters of the access control devices in different areas of the school, a density threshold is set to distinguish high-density areas and low-density areas. For example, set the density threshold as 0.003 access control devices per square meter. Compare the space distribution density of each area with the threshold, and the density higher than the threshold is the high-density area, and the density lower than the threshold is the low-density area. For example, the density of the teaching area is 0.005 access control devices per square meter, which is higher than the threshold, and is a high-density area; while the density of the gym area is 0.002 access control devices per square meter, which is lower than the threshold, and is a low-density area. The high-density area has more and concentrated distribution of access control devices, and may involve multiple important or complex functional places, so a smaller and more accurate space range can be allocated to each access control device to achieve fine management. For example, the space range of the access control device at the entrance of each classroom in the teaching building can be limited to the entrance of the classroom and the indoor area, and the space range radius is set to about 2 meters. The access control devices in the low-density area are relatively scattered and less in number, and may be some entrances or single-function areas, so a relatively larger space range can be allocated to each access control device. For example, the space range of the access control device at the entrance of the school gate connected with the outside can be set as a 5-meter radius area centered on the access control device, covering the school gate and the surrounding road range where personnel may enter. According to the above rules, the corresponding space range of the access control device in different areas is allocated to obtain the initial space range. According to the average daily access time distribution parameters of the school personnel, the peak access time of the personnel is identified, such as 7-9 am, 11-13 pm, 17-19 pm, etc. In the peak access time, the personnel access frequently, in order to ensure the access efficiency and safety, the effective time range of the virtual key can be appropriately relaxed, or the access control device access permission quantity can be increased. In the period with less personnel access, such as 23 pm to 5 am, the access permission of the virtual key can be tightened, the effective time range can be shortened, or the access control device access of some areas can be limited. The initial time range is determined by combining the above time allocation rules and access time distribution parameters.For example, for the access control equipment of the teaching area, according to the teaching arrangement and the personnel access peak period, the initial effective time range of the virtual key is set as 6:00 am to 23:00 pm on weekdays; and for the access control equipment of the dormitory area, considering the life regularity of students, it is set as 24 hours a day, but the virtual key authority of external personnel can be limited during the late night period.

[0086] Specifically, the collected various parameters provide rich data support for subsequent dynamic adjustment of permissions, analysis of abnormal behaviors, etc., helping to realize intelligent and refined access control permission management. Precise permission configuration reduces the cumbersome process of user application and permission adjustment, improves the efficiency of access, ensures the safety of the campus, and creates a convenient and safe campus environment. Whether the number of virtual keys, the spatial range or the time range is determined, it follows the principle of on-demand allocation to ensure that the resource input is accurately matched with the actual demand, avoiding resource idling or deficiency.

[0087] Specifically, as shown in Figure 3 The process of step S2 includes:

[0088] Step S21, according to the initial parameters, obtaining the historical access records corresponding to the user, and obtaining the historical abnormal records of the user according to the real-time request information of the user;

[0089] Specifically, all access records of the user in the past period of time are extracted from the system database or log, including successful and failed attempts, access time, access location (access control ID or area), virtual key version used, etc. These records reflect the user's regular access mode and habits. From the system database or log, extract the access behavior records of the user marked as abnormal in the past period of time, for example: multiple failed attempts, access in unauthorized time / area, records of temporary suspension or adjustment of permissions, etc. These records reflect the user's past risky behavior or permission change.

[0090] Step S22, taking the initial space range, the initial time range, the historical access records and the initial ID as inputs to build a probability prediction model to predict the probability value of the user accessing each sub-area in the initial space range within the initial time range to obtain a prediction result;

[0091] Specifically, a pre-trained probability prediction model (e.g., a model based on time series analysis, user profiling, or collaborative filtering) is used, which can understand the user's historical behavior (historical access records from S21) and the initial spatial and temporal range set. The initial spatial range (defines the geographical boundary of the prediction). The initial time period range (defines the time window of the prediction), the user's historical access records (used to learn the user's access habits), and the initial ID (used for the extraction or association of user features in the model) are input into the probability prediction model. After the model runs, a prediction result is output. This result is usually a probability distribution showing the predicted probability value of the user accessing each (or each sub) region within the initial spatial range within the initial time period. For example, a dictionary or matrix is output, with the region identifier as the key / row and the corresponding access probability as the value / column.

[0092] Step S23, constructing a risk assessment model with the real-time request information and the historical abnormal record as input to evaluate the risk score of the current request information to obtain an evaluation result;

[0093] Specifically, a risk assessment model is constructed to take real-time request information and historical abnormal records as input, to evaluate the risk level of the current request by analyzing the user's current request access time and target area information, combined with the user's past historical abnormal records. Specifically, first, feature extraction is performed on the real-time request information and the historical abnormal record, including whether the access time is in the peak period, whether the target area belongs to the high-sensitive area, etc. 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 for predicting the risk score of the current request information.

[0094] Step S24, constructing a suggestion model with the historical access record, the permission change history in the historical data, and the initial parameters as input to output an optimization suggestion to obtain a suggestion result;

[0095] Specifically, a suggestion model is constructed to take historical access records, permission change history, and initial parameters as input, to provide an optimization suggestion for the user by analyzing the user's historical access patterns and permission change situations, combined with information such as spatial range and time period range in the initial parameters. For example: "Suggest expanding the access area to X area", "Suggest removing access permissions to Z area in Y time period", "Suggest extending the permission validity period to D days", etc. These suggestions aim to make the permissions more in line with the user's actual needs or in line with historical management strategies.

[0096] Step S25, comprehensive analysis according to the prediction result, the evaluation result, and the suggestion result to obtain the initial permission result.

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

[0098] In step S251, the access probability values of each sub-region are extracted according to the prediction result, and the access demand intensity of the user in each sub-region is judged according to a preset probability threshold value, and the sub-region with an access probability value greater than the probability threshold value is marked as a core access region.

[0099] Specifically, the probability value of the user accessing each sub-region in the initial space range within the initial time range is obtained. These probability values are usually presented in the form of a matrix or a list, each sub-region corresponding to a probability value representing the likelihood of the user accessing the sub-region. For example, the prediction result shows that the user's access probability in sub-region A is 0.8, and the access probability in sub-region B is 0.4, etc. According to the campus safety management strategy and the actual traffic demand, a probability threshold value is preset to judge the access demand intensity of the user to each sub-region. For example, if the probability threshold value is set to 0.6, it means that the sub-region with an access probability greater than 0.6 is considered to be a core access region with higher access demand of the user. The sub-regions with an access probability value greater than the preset probability threshold value are marked as core access regions. For example, according to the above prediction result and threshold setting, the access probability of sub-region A is 0.8, which is greater than the threshold value 0.6, so sub-region A is marked as a core access region. In this way, the region that the user is most likely to access in a specific time period can be determined, providing a key reference for subsequent permission allocation.

[0100] In step S252, the risk scores in the evaluation result are graded, a risk threshold value interval is set to obtain a risk judgment result, wherein,

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

[0102] Specifically, a risk threshold interval is set to divide the risk levels. Reasonable thresholds are usually determined based on historical data, performance of risk assessment models, and campus security policies. For example, set the first risk threshold to 0.3 and the second risk threshold to 0.6. This means that a risk score below 0.3 is a low-risk request; greater than or equal to 0.3 and less than 0.6 is a medium-risk request; greater than 0.6 is a high-risk request. It should be noted that the setting of the threshold should be fully analyzed and verified to ensure that it can effectively distinguish between requests of different risk levels. According to the interval in which the risk score is located, the risk judgment result is determined. For example, if a request has a risk score of 0.2, it is judged to be a low-risk request; if the risk score is 0.5, it is judged to be a medium-risk request; if the risk score is 0.7, it is judged to be a high-risk request. Different risk levels of requests will correspond to different permission allocation strategies, such as high-risk requests may require more stringent approval processes or limit access permissions.

[0103] Step S253, converting the optimization suggestions in the suggestion result into parameter adjustment instructions;

[0104] Specifically, the optimization suggestions may include increasing or decreasing access permissions to certain areas, adjusting access time ranges, increasing or decreasing permission levels, etc. For example, the suggestion model may suggest increasing the user's access permissions to a specific area of the library, or suggest extending the user's access time in a certain teaching building. Convert the optimization suggestions into specific parameter adjustment instructions. This requires a clear correspondence between each permission parameter in the system and the adjustment rules. For example, for the suggestion of increasing access permissions, convert it into adding the corresponding area permission parameter in the target version of the virtual key; for the suggestion of adjusting the access time, convert it into an instruction 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 can be accurately implemented into the permission configuration.

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

[0106] Specifically, considering that the core access area reflects the normal access demand of the user, the risk judgment result embodies the security of the request, and the parameter adjustment instruction provides the optimization direction. For example, if the core access area of a request is the teaching building A area, the risk judgment result is low risk, and the parameter adjustment instruction suggests increasing the access permission of the area, then in the comprehensive analysis, the user will be inclined to be given greater access permission. In the comprehensive analysis process, different factors can be assigned weights to highlight their importance in the permission decision. For example, set the weight of the core access area to 0.4, the weight of the risk judgment result to 0.3, and the weight of the parameter adjustment instruction to 0.3. According to the weights and specific performances of different factors, weighted calculation or logical judgment is performed to finally determine the initial permission result of the user. For example, for the above low-risk request, and the core access area and the parameter adjustment instruction both support increasing the permission, after weighted calculation, it is decided to give the user full access permission to the teaching building A area; while for a high-risk request, even if the core access area has higher demand, its access permission can be limited or further approval is required. According to the result of comprehensive analysis, the initial permission result of the user is generated. The initial permission result should clearly indicate the user's access permission in each sub-area, including the range of allowed access area, access time range, permission level, etc.

[0107] Specifically, by extracting the access probability value and marking the core access area, the system can accurately grasp the main activity range of the user, provide strong support for the permission configuration of key areas, and at the same time avoid excessive allocation of permissions, improving the fine degree of permission management. The risk score is processed by grading, so that the system can adopt differentiated permission control strategies according to different risk levels. The optimization suggestion is converted into specific parameter adjustment instruction, enhancing the executability of the suggestion, ensuring that the optimization measures can be accurately implemented into the permission configuration, timely improving and optimizing the permission management strategy, adapting to the changes of campus environment and user demand. Considering the core access area, risk judgment result and parameter adjustment instruction, the relationship between user demand and security management is fully balanced. While meeting the reasonable access demand of the user, the risk is effectively controlled, and the generated initial permission result is more reasonable and reliable, providing a strong guarantee for the stable operation of the campus access control system.

[0108] Specifically, as shown in Figure 4 The process of step S3 includes:

[0109] Step S31, collecting feedback information related to the initial permission result, the feedback information including the user's experience of using the virtual key permission, the difficulty of permission application, and the rationality of permission allocation;

[0110] Specifically, user feedback is collected through various means such as online questionnaire platforms, feedback modules within the access control system, campus forums, emails, and offline suggestion boxes, making it convenient for different user groups to provide feedback. Fixed time periods (e.g., monthly or quarterly) are set to proactively send feedback requests to users, improving the comprehensiveness and timeliness of feedback information.

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

[0112] Specifically, infrared thermal sensors, video surveillance systems, or facial recognition data recording devices are installed to monitor the personnel flow in the area where the access control device is located in real time, and the number of people entering and leaving different time periods and different areas is counted. The access time of all users is automatically recorded by the access control system background to form data records of access time distribution. By analyzing these data, the distribution of peak and off-peak periods can be understood. Deploy device status monitoring modules to collect real-time operating data of access control devices, such as online duration, power outage times, network connection stability, etc. At the same time, record the regular maintenance and repair of the device. Establish a security event reporting system to ensure that all security events (such as illegal intrusion, abuse of authority, etc.) are recorded by on-site security personnel or system automatic detection mechanism, including event time, location, handling measures, etc.

[0113] Step S33, analyzing the feedback information and the environmental data to determine whether the initial parameters need to be adjusted, and if adjustment is needed, adjusting at least one parameter in the initial parameters according to the preset parameter adjustment rule to obtain the adjustment result.

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

[0115] Step S331, quantitatively analyzing the feedback information, setting a threshold for user experience satisfaction, and adjusting the initial parameters when the proportion of negative evaluations in the feedback information exceeds the threshold;

[0116] Step S332, dynamically monitoring the environmental data, setting abnormal thresholds for personnel flow, access time, and security events, and adjusting the initial parameters when any indicator exceeds the abnormal threshold;

[0117] Step S333, according to the preset parameter adjustment rule, adjusting at least one parameter in the initial parameters for different feedback information types and environmental data abnormal situations, respectively, or in combination.

[0118] Specifically, the collected feedback information is classified and organized to establish a quantitative index system. For example, the user's feedback on the use experience of virtual key permissions, the difficulty of permission application, and the rationality of permission allocation are quantified as different indicators. According to the campus management goals and historical data of user satisfaction surveys, set the threshold of user experience satisfaction. For example, set the threshold of dissatisfaction as less than 60%. Calculate the quantitative score of each feedback indicator. When the proportion of negative evaluations exceeds the set threshold, trigger the initial parameter adjustment process. Through the installation of personnel flow sensors or video monitoring systems in access control areas, real-time monitoring of personnel flow changes. Set the abnormal threshold of personnel flow, for example, set the abnormal value of more than 1000 person-time per hour in a certain area, which may indicate that the access demand of the area has increased, and the permission configuration needs to be adjusted. Use access time data recorded by the access control system to analyze the access time distribution. Set the abnormal threshold of access time, such as setting the access request of a certain area during non-working hours exceeding a certain number (such as more than 50 times per hour) as abnormal, which may need to adjust the access time permission of the area. Establish a security event monitoring system to collect security event records in real time. Set the abnormal threshold of security events, such as setting more than 3 security events per month in a certain area as abnormal, indicating that the permission configuration of the area may have security risks and needs to adjust the initial parameters. For different types of feedback information or environmental data anomalies, develop corresponding single-factor adjustment rules. For example, when feedback information indicates that the difficulty of permission application is below the threshold, adjust the parameters related to the permission application process, simplify the application steps, or add application guidelines, etc. When multiple types of feedback information or environmental data anomalies occur simultaneously, develop combined adjustment rules. For example, when the feedback information shows that users are not satisfied with the rationality of permission allocation and environmental data monitoring shows that personnel flow is abnormal, it may be necessary to adjust the spatial range and access time range parameters of the virtual key at the same time.

[0119] Specifically, the user feedback information is quantitatively analyzed, and a clear satisfaction threshold is set to make the decision-making process more objective and avoid subjective bias, ensuring that necessary adjustments are made only when user satisfaction is significantly decreased. Through dynamic monitoring of environmental data and setting of abnormal thresholds, the system can identify potential security risks and operational problems and adjust parameters in a timely manner to prevent further deterioration of the problem and ensure campus safety. According to the preset parameter adjustment rules, single or combined parameter adjustments can be made flexibly according to different types of feedback information and environmental data anomalies, ensuring that the adjustment measures are accurate and effective, and avoiding over-adjustment or insufficient adjustment.

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

[0121] Step S41, map the adjustment result and the initial permission result to identify the permission items that need to be adjusted to obtain an identification result.

[0122] Specifically, the adjustment result is compared with the initial permission result in detail to identify the permission items that need to be adjusted. For example, if the adjustment result indicates that the access time of a certain area needs to be extended, it is identified that the access time permission item of the area needs to be adjusted. According to the comparison result, all the permission items that need to be adjusted are listed, including their specific values in the initial permission result and target values in the adjustment result. For example, the access time of a certain area in the initial permission result is 8:00-18:00, and the adjustment result requires it to be changed to 7:00-19:00, so this access time permission item is identified as needing adjustment.

[0123] Step S42, modifying the identification result according to the adjustment result to obtain a modified result;

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

[0125] Step S421, locating the corresponding permission item in the identification result according to the parameter modification instruction specified in the adjustment result;

[0126] Specifically, the format of the parameter modification instruction in the adjustment result is analyzed to determine the types and structures of the information contained in the instruction, such as permission item identification, modification type (update or calculation), modification value or rule, etc. The permission item identification that needs to be adjusted is extracted from the modification instruction, which is used to accurately locate the corresponding permission item in the initial permission result. For example, the permission item identification can be a sub-area ID, an access time period code, etc. A mapping relationship between the parameter modification instruction and the permission item in the initial permission result is established, and the corresponding permission item is found in the data structure (such as a list, a dictionary, etc.) of the initial permission result through the permission item identification. According to the extracted permission item identification, the specific permission item is searched and located in the initial permission result. For example, the permission item matching the given sub-area ID is searched in the permission item list.

[0127] Step S422, updating the specific parameter value of the located permission item in the identification result according to the modification value or modification rule in the parameter modification instruction, or calculating;

[0128] Specifically, if a specific modification value is specified in the modification instruction, the current value of the located permission item is directly replaced by the new modification value. For example, the access permission of a certain sub-area is changed from "read only" to "read and write". If a modification rule is provided in the modification instruction, the current value of the permission item is calculated according to the rule to obtain a new parameter value. For example, the rule can be "extend the access time by 3 minutes", then the new end time needs to be calculated.

[0129] Step S423, verifying whether the modified permission item meets the preset permission rules and format requirements;

[0130] Specifically, it is verified whether the modified permission item meets the preset permission rules, such as the access time cannot exceed the maximum range allowed by the system, the spatial range must be an area existing in the campus, etc. It is checked whether the modified permission item meets the data format requirements, such as whether the time format is correct, whether the area ID exists, etc.

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

[0132] Step S424, the modified permission item that passes the verification is determined as the modification result.

[0133] Specifically, the modified permission item that passes the verification is recorded to form the modification result. The modification result should include the identification of the permission item, the modified value, etc. In the target version of the virtual key, the information of the related permission item is updated to ensure that the target version reflects the latest modification result.

[0134] Step S43, the modification result is combined with the unadjusted permission item to generate the target version of the virtual key.

[0135] Specifically, according to the initial permission result, those permission items that are not marked as needing adjustment in step S41 are identified. These permission items remain unchanged in their original state. The modification result generated in step S42 (i.e. the updated permission item set) is combined with the unadjusted permission item set identified in step 1 (initial parameters). During the combination process, it is checked whether there is redundancy (e.g. two identical permissions for the same access control) or conflict (e.g. both allowing and prohibiting permissions for one access control) of the permission items, and cleaned up or resolved according to the preset rules (usually the more lenient or latest permission is retained). The final combined and cleaned up permission item set 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 and adjusted permission information.

[0136] Specifically, by mapping and matching the adjustment result with the initial permission result, the permission items that need to be adjusted are accurately identified, ensuring the pertinence and effectiveness of the adjustment operation. The modified permission items are organically combined with the unadjusted permission items to form a complete target version of the virtual key, ensuring the comprehensiveness and accuracy of the permission configuration. It can quickly locate the permission items that need to be adjusted, improve the adjustment efficiency, and shorten the response time. According to the modification instruction, the parameter value update or calculation is flexibly executed, which adapts to various adjustment requirements and improves the flexibility and adaptability of the system. Through accurate and timely permission adjustment, it ensures that users obtain reasonable access permissions, improves user experience and satisfaction.

[0137] In another aspect, the present application provides a virtual key management-based access control permission management system, characterized in that it comprises:

[0138] 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;

[0139] A version generation module is connected to the attribute definition module, 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;

[0140] A data collection module is connected to the version generation module, 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;

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

[0142] A permission verification module is connected to the parameter adjustment module, configured to assign the target version to a user, or set the target version for the user to independently obtain, and perform permission verification according to the user and the target version.

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

[0144] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to related technical features without departing from the principles of the present application, and the technical solutions after the changes or replacements will fall within the protection scope of the present application.

[0145] The above description is only for the preferred embodiments of the present application and is not intended to limit the present application; for those skilled in the art, the present application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for access control authority management based on virtual key management, characterized in that: include: Step S1 is used to obtain initial attributes defining a virtual key to obtain initial parameters, including an initial ID, an initial name, an initial state, an initial validity period, an initial spatial range, and an initial time range. The initial number of virtual keys, historical user data, and real-time user request information are also obtained. Step S2, generating an initial version of the virtual key according to the initial parameters, and performing calculations based on a pre-trained machine learning model to obtain an initial permission result; Step S3, for collecting feedback information related to the initial permission result, or adjusting at least one of the initial parameters according to environmental data to obtain an adjustment result; Step S4, adjusting the initial authority result according to the adjustment result to generate a target version of the virtual key; Step S5: assign the target version to the user, or set it for the user to claim it independently, and perform permission verification based on the user and the target version.

2. The access control authority management method based on virtual key management according to claim 1 is characterized in that: The process of step S1 includes: 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 entry and exit time distribution parameters of personnel; Step S12, determining the initial number of virtual keys according to the type distribution parameter number, allocating corresponding spatial ranges to access control devices in different areas according to the spatial distribution density parameter to obtain the initial spatial range, and determining the initial time period range according to the entry and exit time period distribution parameter.

3. The access control authority management method and system based on virtual key management according to claim 2 is characterized in that: The process of step S12 includes: Step S121, determining the initial quantity according to the type distribution parameter and the preset number of virtual keys allocated to each type of personnel; Step S122: identifying high-density areas and low-density areas according to the spatial density distribution parameters, and allocating corresponding initial spatial ranges to access control devices in different areas in accordance with a preset spatial allocation rule; Step S123: determining the initial time range according to the entry and exit time period distribution parameters in combination with a preset time allocation rule.

4. The access control authority management method based on virtual key management according to claim 3 is characterized in that: The process of step S2 includes: Step S21, obtaining the user's corresponding historical access records based on the initial parameters, and obtaining the user's historical abnormality records based on the user's real-time request information; Step S22, using the initial spatial range, the initial time range, the historical access records, and the initial ID as input to construct a probability prediction model to predict the probability of the user visiting each sub-area within the initial spatial range within the initial time range to obtain a prediction result; Step S23, using the real-time request information and the historical exception records as input to construct a risk assessment model to evaluate the risk score of the current request information to obtain an assessment result; Step S24, using the historical access records, the permission change history in the historical data, and the initial parameters as input to construct a suggestion model to output optimization suggestions to obtain suggestion results; Step S25: Perform a comprehensive analysis based on the prediction result, the evaluation result, and the recommendation result to obtain the initial authority result.

5. The access control authority management method based on virtual key management according to claim 4 is characterized in that: The process of step S25 includes: Step S251: extracting the access probability value of each sub-area based on the prediction result, and judging the intensity of the user's access demand in each sub-area according to a preset probability threshold, and marking the sub-area with the access probability value greater than the probability threshold as a core access area; Step S252: grading the risk scores in the assessment results and setting risk threshold intervals to obtain risk judgment results, wherein: If the risk score is lower than the first risk threshold, the request is determined to be low risk; if the risk score is greater than or equal to the first risk threshold and less than the second risk threshold, the request is determined to be medium risk; if the risk score is greater than the second risk threshold, the request is determined to be high risk; Step S253, converting the optimization suggestions in the suggestion results into parameter adjustment instructions; Step S254 , comprehensively generating an initial permission result based on the core access area, the risk judgment result, and the parameter adjustment instruction.

6. The access control authority management method based on virtual key management according to claim 5 is characterized in that: The process of step S3 includes: Step S31, collecting feedback information related to the initial permission result, the feedback information including the user's experience of using the virtual key permission, the difficulty of permission application, and the rationality of permission allocation; Step S32: Collect environmental data, including personnel flow changes, access time distribution, equipment operation status, and security event records in the area where the access control equipment is located; 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 of the initial parameters according to a preset parameter adjustment rule to obtain the adjustment result.

7. The access control authority management method based on virtual key management according to claim 6 is characterized in that: The process of step S33 includes: Step S331: Quantitatively analyze the feedback information, set a threshold for user experience satisfaction, and adjust the initial parameters when the proportion of negative reviews in the feedback information exceeds the threshold; Step S332, dynamically monitoring the environmental data, setting abnormal thresholds for personnel flow, access time, and security events, and adjusting the initial parameters when any of the monitored indicators exceeds the abnormal threshold; Step S333 : According to preset parameter adjustment rules, at least one of the initial parameters is adjusted separately or in combination for different feedback information types and abnormal environmental data conditions.

8. The access control authority management method based on virtual key management according to claim 7 is characterized in that: The process of step S4 includes: Step S41, mapping and matching the adjustment result with the initial permission result to identify the permission item that needs to be adjusted to obtain an identification result; Step S42, modifying the recognition result according to the adjustment result to obtain a modified result; Step S43: combining the modification result with the unadjusted permission item to generate a target version of the virtual key.

9. The access control authority management method based on virtual key management according to claim 8, characterized in that: 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: updating or calculating specific parameter values ​​of the permission items located in the identification results according to the modification values ​​or modification rules in the parameter modification instruction; Step S423: Verify whether the modified permission item complies with preset permission rules and format requirements; Step S424: Determine the modified permission item that passes verification as the modification result.

10. A virtual key management-based access control authority management system based on the virtual key management-based access control authority management method according to any one of claims 1 to 9, characterized in that: include: An attribute definition module is used to obtain and define the initial attributes of the virtual key to obtain initial parameters, including an initial ID, an initial name, an initial state, an initial validity period, an initial spatial range, and an initial time range. It is also used to obtain the initial number of virtual keys, historical user data, and real-time user request information. A version generation module, connected to the attribute definition module, generates an initial version of the virtual key according to the initial parameters, and calculates based on a pre-trained machine learning model to obtain an initial permission result; a data collection module, connected to the version generation module, for collecting feedback information related to the initial permission result, or adjusting at least one of the initial parameters using environmental data to obtain an adjustment result; a parameter adjustment module, connected to the data collection module, and adjusting the initial permission result according to the adjustment result to generate a target version of the virtual key; The authority verification module is connected to the parameter adjustment module, allocates the target version to the user, or sets it for the user to obtain it independently, and performs authority verification based on the user and the target version.

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