A government-enterprise multi-level permission control method and system

Abstract

The application provides a silver government-enterprise multi-level permission control method and system, solves the problem of dynamic permission adaptation and control of heterogeneous systems by constructing an emergency permission object and a permission semantic adaptation gateway for semantic conversion and local execution feedback, can realize dynamic permission semantic adaptation and control of cross-institution heterogeneous systems in an emergency scene, and has the advantages of improving the flexibility and adaptability of permission changes.

Description

Technical Field

[0001] This application relates to cross-institutional collaborative access control technology, specifically to multi-level access control between banks, government, and enterprises. Background Technology

[0002] In responding to large-scale natural disasters and other public emergencies, government emergency command departments, local governments, multiple banks, and numerous enterprises need to coordinate emergency resources and allocate funds through a unified collaborative platform. In this specific scenario, challenges arise from the heterogeneous technical architectures and vastly different access control models of the participating systems. Each party's business systems often operate independently, with relatively fixed internal access control configurations, making it difficult to adapt to the dynamic and temporary access control changes required in emergency situations.

[0003] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0004] The purpose of this application is to provide a multi-level access control method and system for banks, government and enterprises, which has the advantages of enabling dynamic semantic adaptation and control of access control across heterogeneous systems in emergency scenarios, and improving the flexibility and adaptability of access control changes.

[0005] This application provides a multi-level access control method for banks, government, and enterprises, with the following technical solution:

[0006] An emergency permission object is constructed and sent to the permission semantic adaptation gateway. The emergency permission object includes standard permission information and emergency scenario information. The permission semantic adaptation gateway is deployed at the access layer of participating institutions (banks, governments, and enterprises) to receive and parse the emergency permission object. Based on the emergency scenario information, the permission semantic adaptation gateway selects a preset permission mapping strategy and converts the emergency permission object into a domain permission instruction according to the permission mapping strategy and specific domain mapping rules, and sends the domain permission instruction to the local machine. The domain permission instruction is a permission instruction applicable to banks, governments, and enterprises. The gateway receives the domain permission instruction, converts it into a locally executable operation, and feeds back the execution result to the permission semantic adaptation gateway.

[0007] Furthermore, this application proposes that emergency scenario information includes emergency parameters; based on the emergency scenario information, the permission semantic adaptation gateway selects a preset permission mapping strategy, including: performing integrity verification on the emergency scenario information; performing semantic analysis and standardization processing on the emergency parameters according to a preset emergency parameter semantic library; detecting whether there are conflicts between the standardized emergency parameters; if there are conflicts, adjudicating the conflicting parameters according to preset priority rules to obtain the final emergency parameters; selecting or adjusting the permission mapping strategy based on the final emergency parameters; evaluating the confidence level of the permission mapping strategy selected or adjusted based on the final emergency parameters; if the confidence level is lower than a preset threshold, triggering a manual review process to confirm or correct the permission mapping strategy.

[0008] Furthermore, this application proposes to assess the confidence level of the permission mapping strategy selected or adjusted based on the final emergency parameters. If the confidence level is lower than a preset threshold, a manual review process is triggered to confirm or correct the permission mapping strategy. This includes: assessing the confidence level of the selected or adjusted permission mapping strategy based on the final emergency parameters to obtain the confidence level; obtaining scenario evolution information characterizing the dynamic evolution of the emergency scenario, as well as risk level information of the permission operation types associated with the selected or adjusted permission mapping strategy; adjusting the preset threshold according to the scenario evolution information and risk level information to obtain the adjusted threshold; and triggering a manual review process to confirm or correct the permission mapping strategy if the confidence level is lower than the adjusted threshold.

[0009] Furthermore, this application proposes that locally executable operations are executed based on a local permission execution agent; receiving domain permission instructions and converting them into locally executable operations, and feeding back the execution results to the permission semantic adaptation gateway, including: after executing the domain permission instructions received from the permission semantic adaptation gateway, the local permission execution agent generates execution result information containing the instruction identifier, execution completion status, and execution completion timestamp; the local permission execution agent stores the execution result information in a local storage unit and sends it to the permission semantic adaptation gateway; the local storage unit records each execution result information and its sending status; the local permission execution agent iterates through the execution result information recorded in the local storage unit that has not yet received successful confirmation from the permission semantic adaptation gateway according to a preset check cycle, and resends it to the permission semantic adaptation gateway; after distributing the domain permission instructions to the local permission execution agent, the permission semantic adaptation gateway starts a feedback waiting timer for the instruction; if no valid execution result feedback is received from the local permission execution agent within a preset timeout period, the permission semantic adaptation gateway temporarily marks the execution status of the domain permission instruction as pending determination.

[0010] Furthermore, this application proposes receiving domain permission instructions, converting them into locally executable operations, and feeding back the execution results to the permission semantic adaptation gateway. This also includes: when multiple consecutive instruction feedback times out or the system load is low, proactively initiating a status query request to the corresponding local permission execution agent for domain permission instructions with a pending status; the query request contains a unique identifier of the original domain permission instruction; after receiving the status query request from the permission semantic adaptation gateway, the local permission execution agent retrieves the execution result information corresponding to the requested instruction identifier from its local persistent storage unit and returns the retrieved information to the permission semantic adaptation gateway; the permission semantic adaptation gateway updates the final execution status of the corresponding domain permission instruction maintained internally based on the execution result information proactively fed back by the local permission execution agent, or the execution result information obtained through proactive querying; the final execution status will be used to generate a global permission view and report it to the emergency command platform.

[0011] Furthermore, this application proposes adjusting a preset threshold based on scenario evolution information and risk level information to obtain an adjusted threshold, including: if the adjustment direction indicated by the scenario evolution information is inconsistent with the adjustment direction indicated by the risk level information, obtaining the first adjustment intention formed by each scenario evolution factor included in the scenario evolution information on the preset threshold, and the second adjustment intention formed by the risk level information on the preset threshold; both the first and second adjustment intentions include adjustment trends and adjustment magnitudes; determining whether there is a conflict in adjustment trends between the first adjustment intentions formed by each scenario evolution factor, and whether there is a conflict in adjustment trends between the adjustment intention formed by the scenario evolution information and the adjustment intention formed by the risk level information; when a conflict in adjustment trends is determined, invoking the conflict resolution logic within a preset emergency response strategy set to prioritize and integrate the conflicting adjustment intentions, and outputting the dominant adjustment intention; determining the net adjustment effect value based on the dominant adjustment intention and the preset influence factors associated with each dominant adjustment intention; and adjusting the preset threshold based on the net adjustment effect value to generate the adjusted threshold.

[0012] Furthermore, this application proposes that when a conflict is determined to exist, a conflict resolution logic within a pre-set emergency response strategy set is invoked to prioritize and integrate the conflicting adjustment intentions, and output a dominant adjustment intention. This includes: determining the degree of matching between the current combination of conflicting adjustment intentions and each conflict resolution rule within the pre-set emergency response strategy set; determining the priority of the emergency target corresponding to the current emergency scenario information based on the degree of matching; adjusting the priority determination parameters of the conflict resolution rules within the pre-set emergency response strategy set or selecting a backup resolution rule within the pre-set emergency response strategy set that is compatible with the current emergency target based on the priority of the emergency target, so as to form an adaptive conflict resolution configuration for the current combination of conflicting adjustment intentions; and prioritizing and integrating the conflicting adjustment intentions based on the adaptive conflict resolution configuration, and outputting a dominant adjustment intention.

[0013] Furthermore, this application also proposes that the method further includes a domain-specific mapping rule management step; the domain-specific mapping rule management step includes: in response to the submission of an edited domain-specific mapping rule or the addition of a new domain-specific mapping rule, based on pre-configured logical judgment rules, detecting whether there is a configuration-level conflict or inconsistency between the newly submitted content and other existing rules in the rule base, and outputting the detection result; the logical judgment rules include the overlap of rule application conditions, the mutual exclusivity of permission operations, and the sequential dependency of rule execution.

[0014] Furthermore, this application proposes that the data structure of the emergency permission object be defined using an extensible markup language or JSON format.

[0015] Furthermore, this application also proposes a multi-level access control system for banks, government, and enterprises, comprising: a construction module for constructing emergency access objects and sending them to an access semantic adaptation gateway; the emergency access objects include standard access information and emergency scenario information; the access semantic adaptation gateway is deployed at the access layer of participating institutions in the bank-government-enterprise system to receive and parse the emergency access objects; a conversion module for selecting a preset access mapping strategy based on the emergency scenario information, and converting the emergency access objects into domain access instructions based on the access mapping strategy and specific domain mapping rules, and sending the domain access instructions to the local machine; the domain access instructions are access instructions applicable to banks, government, and enterprises; and an execution module for receiving the domain access instructions and converting them into locally executable operations, and feeding back the execution results to the access semantic adaptation gateway.

[0016] As can be seen from the above, the multi-level permission control method and system provided in this application solves the problem of dynamic adaptation and control of permissions in heterogeneous systems by constructing emergency permission objects, permission semantic adaptation gateways for semantic conversion and local execution feedback. It has the advantages of being able to realize dynamic permission semantic adaptation and control of cross-organizational heterogeneous systems in emergency scenarios, and improving the flexibility and adaptability of permission changes. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the steps of the multi-level access control method for banks, government, and enterprises disclosed in an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram of the system structure of the multi-level access control method for banks, government, and enterprises disclosed in an embodiment of the present invention. Detailed Implementation

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which these embodiments belong; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to limit these embodiments; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of these embodiments are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or accompanying drawings of these embodiments are used to distinguish different objects, not to describe a particular order.

[0021] The implementation details of the technical solution in this embodiment are described below:

[0022] This application proposes a multi-level access control method for banks, government, and enterprises, such as... Figure 1 As shown, the method includes:

[0023] S101, construct an emergency permission object and send the emergency permission object to the permission semantic adaptation gateway; the emergency permission object includes standard permission information and emergency scenario information; the permission semantic adaptation gateway is deployed in the access layer of participating institutions of banks, government and enterprises to receive and parse the emergency permission object;

[0024] S102, based on the emergency scenario information, the permission semantic adaptation gateway selects a preset permission mapping strategy, and converts the emergency permission object into a domain permission instruction according to the permission mapping strategy and specific domain mapping rules, and sends the domain permission instruction to the local machine; the domain permission instruction is a permission instruction applicable to banks, government and enterprises.

[0025] S103 receives domain permission instructions and converts them into locally executable operations, then feeds back the execution results to the permission semantic adaptation gateway.

[0026] Among them, the emergency permission object refers to a specially designed data structure used to encapsulate request information that needs to be adjusted or configured in emergency scenarios. It can be defined using Extensible Markup Language (XML) or JSON format, such as an XML document containing fields such as user ID, target system identifier, required permission type, and effective time limit. Its main purpose is to carry the intention of permission change transmitted across heterogeneous systems.

[0027] Standard permission information refers to data that describes permission requirements in a general and abstract way. It can be represented by a role-based access control (RBAC) model, an attribute-based access control (ABAC) model, or a capability model. For example, "granting user A permission to perform operation C on system B" is mainly to provide a permission description basis that is independent of the specific target system.

[0028] Emergency scenario information refers to data describing the background, environment, and constraints of the current emergency event. It may include parameters such as disaster type, occurrence area, emergency response level, scope of involved institutions, and time window. For example, "flood disaster, area code XYZ, level 1 response, involving banks, government, and enterprises." Its main purpose is to provide contextual basis for the dynamic adaptation of permissions.

[0029] Among them, the permission semantic adaptation gateway refers to a middleware or service component deployed at the network access layer that is responsible for receiving, parsing and converting permission instructions. It can be implemented as an independent server application, containerized service or embedded module, such as a microservice that receives HTTP requests and executes internal logic. Its main purpose is to serve as a permission instruction conversion hub between heterogeneous systems.

[0030] Among them, the permission mapping strategy refers to a set of rules that are predefined or dynamically generated to guide how to convert standard permission information and emergency scenario information into permission instructions for a specific domain. It can be represented by lookup tables, decision trees, rule engines or machine learning models. For example, a rule that maps "Level 1 response + material reporting" to "ERP system role X + inventory module write permission" is mainly to provide the logical basis for permission conversion.

[0031] Among them, domain-specific mapping rules refer to more detailed permission conversion rules customized for specific participating institutions or their business systems. These rules can be represented by system API call specifications, database operation instruction templates, or specific application configuration scripts. For example, the general "payment permission escalation" instruction can be converted into a transaction code and authorization limit parameter specific to the bank's core system. The main purpose is to ensure that the converted instruction can be accurately understood and executed by the target system.

[0032] Domain permission instructions refer to permission configuration or operation instructions that are applicable to the business systems of specific participating institutions after being converted by the permission semantic adaptation gateway. They can be represented by system API calls, database update statements, configuration file modification instructions, or specific message formats. For example, an API request that calls the bank system interface to increase the account payment limit is mainly to provide permission operation commands that the target system can directly execute.

[0033] Among them, locally executable operations refer to the further transformation of domain permission instructions into low-level operations that the target system can directly execute after receiving them. These operations may include calling the local permission management module, modifying the user permission table, or triggering specific business processes. For example, updating user roles or permission lists in an ERP system is mainly for the purpose of completing the actual configuration of permissions within the target system.

[0034] In some preferred embodiments, the construction module generates an emergency permission object. For example, this object specifies that, in a flood disaster scenario, a user of an enterprise needs to be granted the permission to report disaster relief material inventory in a specific material management system. This emergency permission object contains standard permission information, such as "User ID: user_A, Operation Type: Report, Resource Type: Disaster Relief Material Inventory," and emergency scenario information, such as "Disaster Type: Flood, Region: XYZ, Response Level: Level 1." This object is sent to the permission semantic adaptation gateway. The conversion module receives the object and parses out the emergency scenario information. Based on scenario information such as "flood" and "Level 1 response," the permission semantic adaptation gateway selects a preset "Flood Level 1 Response Material Reporting" permission mapping strategy. This strategy may instruct the mapping of the general "Report Disaster Relief Material Inventory" permission to a specific API call or database operation in the target material management system. Simultaneously, combining the specific domain mapping rules of the enterprise's materials management system (e.g., the system uses a RESTful API for inventory updates, requiring specific API endpoints and data formats), the permission semantic adaptation gateway converts the emergency permission object into a specific domain permission instruction, such as a JSON-formatted API call request containing API address, user credentials, material type code, and quantity fields. This domain permission instruction is sent to the enterprise's locally deployed materials management system. The execution module receives the JSON request, converts it into an internal API call function, and performs the inventory reporting operation. After the operation is completed, the execution module generates an execution result containing execution status (success / failure), timestamp, and other information, and feeds it back to the permission semantic adaptation gateway.

[0035] In some of the embodiments described above in this application, a preset permission mapping strategy is selected based on emergency scenario information. Specifically, the permission semantic adaptation gateway directly receives the original emergency scenario information and selects the most matching strategy from the preset permission mapping strategy library based on this original information through simple keyword matching or rule lookup. This can quickly respond to emergency needs. However, in its implementation, emergency scenario information may be incomplete, semantically ambiguous, or conflicting. Directly using this information to select the permission mapping strategy may lead to inaccurate strategy selection, thereby affecting the effectiveness and security of permission control.

[0036] In response, this application further proposes the following steps for the permission semantic adaptation gateway to select a preset permission mapping strategy based on emergency scenario information:

[0037] The integrity of emergency scenario information is verified, and semantic analysis and standardization are performed on the corresponding emergency parameters after integrity verification based on the preset emergency parameter semantic library.

[0038] The system detects whether there are conflicts between standardized emergency parameters. If there are conflicts, the conflicting parameters are adjudicated according to preset priority rules to obtain the final emergency parameters.

[0039] Based on the final emergency parameters, select or adjust the permission mapping strategy;

[0040] Assess the confidence level of the permission mapping strategy selected or adjusted based on the final emergency response parameters. If the confidence level is lower than the preset threshold, trigger a manual review process to confirm or correct the permission mapping strategy.

[0041] Emergency scenario information refers to a collection of information describing the current emergency event, environment, and needs, which can be implemented using structured data formats or unstructured text descriptions. Emergency parameters refer to key data items or attributes in the emergency scenario information used to describe specific situations, including event type, geographical location, affected institutions, required resources, and urgency level. Integrity verification checks whether the emergency scenario information contains all necessary parameters and whether the data format of each parameter item meets requirements. This can be done using preset data patterns or verification rules, aiming to ensure the data foundation for subsequent processing is complete and valid. The emergency parameter semantic library is a knowledge base storing standard definitions, synonyms, hierarchical relationships, and value ranges of emergency parameters. It can be a database, configuration file, or ontology model, aiming to provide a basis for semantic analysis and standardization of emergency parameters. Semantic analysis and standardization processing involves parsing the meaning of emergency parameters and converting them into a unified and standardized representation. This can be achieved using natural language processing techniques, rule engines, or by searching the semantic library, aiming to eliminate ambiguity and differences between parameters from different sources and with different expressions. Priority rules refer to preset rules used to resolve the priority of conflicting parameters. These rules can be a priority list, rule set, or decision tree, and their purpose is to determine which parameter should be adopted when parameters conflict. Conflicting parameter adjudication refers to selecting or generating a comprehensive set of parameters from contradictory parameters based on priority rules or other conflict resolution logic. This can be achieved using rule matching, weighted averaging, or expert systems, and its purpose is to obtain a clear and conflict-free final parameter set. Final emergency parameters refer to a reliable set of parameters obtained after integrity verification, semantic analysis, standardization, and conflict adjudication, used for strategy selection. Their purpose is to provide accurate input for subsequent strategy selection. Selecting or adjusting permission mapping strategies refers to selecting the most suitable strategy from a preset strategy library based on the final emergency parameters, or modifying existing strategies to adapt to the current scenario. This can be achieved using rule matching, machine learning models, or case-based reasoning, and its purpose is to map emergency scenario requirements into specific permission operation instructions. Confidence level refers to an evaluation metric for the reliability or applicability of a selected or adjusted permission mapping strategy. It can be calculated based on factors such as the quality of input parameters, the complexity of the processing, and the accuracy of strategy matching. Its purpose is to measure the credibility of the strategy selection result. A preset threshold refers to a pre-defined numerical limit used to determine whether the confidence level is high enough. Its purpose is to set a standard; if it falls below this standard, the strategy selection result is considered to require further confirmation. The manual review process refers to the process of introducing human experts to review, confirm, or modify the strategy selection result when the strategy confidence level is low. Its purpose is to compensate for the shortcomings of automated processing through human judgment, ensuring the accuracy and security of critical decisions.

[0042] In some preferred embodiments, specifically, suppose a bank system needs to temporarily increase the payment limit of an account based on an emergency instruction. The emergency scenario information includes the parameters: "Account ID: 12345", "Operation Type: Increase Limit", "New Limit: 10 million", and "Urgency Level: High". The system first performs a completeness check on the emergency scenario information, confirming that all necessary parameters (Account ID, Operation Type, New Limit) are present and correctly formatted. Next, based on the emergency parameter semantic library, "Increase Limit" is standardized to the internal operation code "OP_INCREASE_LIMIT", "10 million" is standardized to the value "10000000", and "Urgency Level: High" is standardized to the priority flag "PRIORITY_HIGH". When checking for conflicts between the standardized emergency parameters, suppose the system simultaneously receives another instruction for the same account with the parameters "Account ID: 12345", "Operation Type: Freeze Account", and "Urgency Level: Extremely High". The system detects a conflict between "Increase Limit" and "Freeze Account". Based on preset priority rules, such as specifying that "freezing the account" has a higher priority than "increasing the credit limit," the system adjudicates conflicting parameters and adopts the parameters related to "freezing the account" as the final emergency parameters. Based on these final emergency parameters, the system selects the corresponding permission mapping strategy from the strategy library. This strategy maps "freezing the account" to specific API calls and parameter settings in the bank's core system that change the account status. Subsequently, the system evaluates the confidence level of the permission mapping strategy selected or adjusted based on the final emergency parameters. For example, due to parameter conflicts and adjudication, and the high urgency of the original instruction, the system's calculated confidence level may be low, such as 0.7. If the preset threshold is 0.8, since a confidence level of 0.7 is lower than the preset threshold of 0.8, the system triggers a manual review process to confirm or correct the permission mapping strategy. The manual reviewer receives a notification, reviews the original instruction, the conflict situation, the adjudication result, and the system-recommended strategy (freezing the account), and, considering the current emergency situation, confirms whether to execute the freeze operation or modify it to other operations, such as temporarily locking the account pending further instructions.

[0043] This application further proposes steps for assessing the confidence level of the permission mapping strategy selected or adjusted based on the final emergency response parameters. If the confidence level is lower than a preset threshold, a manual review process is triggered to confirm or correct the permission mapping strategy. These steps include:

[0044] Based on the final emergency parameters, assess the confidence level of the selected or adjusted permission mapping strategy to obtain the confidence level;

[0045] Obtain scenario evolution information that characterizes the dynamic evolution of emergency scenarios, as well as risk level information of permission operation types associated with the selected or adjusted permission mapping strategy;

[0046] Based on scenario evolution information and risk level information, the preset threshold is adjusted to obtain the adjusted threshold; if the confidence level is lower than the adjusted threshold, a manual review process is triggered to confirm or correct the permission mapping strategy.

[0047] Among them, scenario evolution information refers to information characterizing the dynamic evolution of emergency scenarios, which may include changes in disaster severity, availability of rescue resources, occurrence of secondary disasters, and changes in public sentiment. Its purpose is to reflect changes in the emergency situation and provide a basis for dynamically adjusting thresholds. Risk level information refers to the risk level information of the permission operation type associated with the selected or adjusted permission mapping strategy. Specifically, it may be a pre-set risk rating or dynamically assessed risk value for a specific permission operation. Its purpose is to measure the potential impact of permission operations and provide a basis for dynamically adjusting thresholds. Adjusting preset thresholds refers to modifying the preset thresholds used to determine whether to trigger manual review based on scenario evolution information and risk level information. Specifically, it may be done by looking up tables, calculating formulas, or predicting using machine learning models, dynamically increasing or decreasing the preset thresholds according to the urgency and risk level of the scenario evolution. Its purpose is to make the triggering conditions for manual review more flexible and intelligent, adapting to the dynamically changing emergency environment.

[0048] In some preferred embodiments, it is assumed that the system assesses a certain permission mapping strategy with a confidence level of 85% based on the final emergency parameters. Simultaneously, the system acquires scenario evolution information, such as indications that the urgency of the current emergency scenario is increasing, possibly manifested as an escalation of the disaster level or the occurrence of secondary disasters. Furthermore, the system acquires risk level information for the permission operation type associated with this permission mapping strategy (e.g., involving large-scale fund disbursements), indicating that the operation belongs to a high-risk category. Based on this scenario evolution information and risk level information, the system dynamically adjusts the preset threshold. For example, if the scenario urgency increases and the operational risk is high, the system can lower the preset threshold from the default 90% to 80%. In this case, since the assessed confidence level of 85% is higher than the adjusted threshold of 80%, the system determines that no manual review is needed and directly applies the permission mapping strategy. Conversely, if the assessed confidence level is 75%, while the adjusted threshold remains at 80%, then since the 75% confidence level is lower than the adjusted threshold of 80%, the system will trigger a manual review process, whereby a human expert will confirm or correct the permission mapping strategy.

[0049] This application further proposes a step-by-step approach to receiving domain permission instructions, converting them into locally executable operations, and feeding back the execution results to the permission semantic adaptation gateway, including:

[0050] After executing the domain permission instruction received from the permission semantic adaptation gateway, the local permission execution agent generates execution result information containing the instruction identifier, execution completion status, and execution completion timestamp. The local permission execution agent stores the execution result information in the local storage unit and sends it to the permission semantic adaptation gateway. The local storage unit records each execution result information and its sending status.

[0051] The local permission execution agent, according to a preset check cycle, traverses the execution result information recorded in the local storage unit that has not yet been successfully received and confirmed by the permission semantic adaptation gateway, and resends it to the permission semantic adaptation gateway.

[0052] After distributing a domain permission instruction to the local permission execution agent, the permission semantic adaptation gateway starts a feedback waiting timer for that instruction. If no valid execution result feedback is received from the local permission execution agent within the preset timeout period, the permission semantic adaptation gateway temporarily marks the execution status of the domain permission instruction as pending.

[0053] The local permission execution agent refers to a software module or process deployed on the local system side, responsible for receiving and executing domain permission instructions and feeding back the execution results to the permission semantic adaptation gateway. It can be implemented as a standalone daemon, embedded library, or plugin. Domain permission instructions refer to the instruction format, after being converted by the permission semantic adaptation gateway, suitable for a specific local system permission management model or interface. They can be carried using data structures such as XML, JSON, or specific binary protocols. Locally executable operations refer to the specific operations performed on the local system after the local permission execution agent further parses the domain permission instructions, such as API calls, script execution, or configuration modifications. These can include adding, deleting, modifying, and querying user permissions, adjusting resource access control policies, or enabling / disabling specific functions. The instruction identifier is a tag used to uniquely identify a domain permission instruction. It can be in the form of a globally unique identifier (UUID), a serial number, or a hash value generated by combining a timestamp and source address. The execution completion status refers to the result of the domain permission instruction's execution on the local system, which can be represented as an enumeration of values ​​such as success, failure, partial success, or execution rejection. The execution completion timestamp is the time record when the local permission execution agent completes the execution of a domain permission instruction. It can use a standard Unix timestamp or an ISO 8601 format time string. Execution result information is a data structure containing key information such as instruction identifier, execution completion status, and execution completion timestamp. It is used to report the execution status of instructions to the permission semantic adaptation gateway and can use a structured message body format. The local storage unit is the storage medium used by the local permission execution agent to persistently store execution result information. It can use a local file system, an embedded database such as SQLite, or an in-memory database. The sending status is a status flag indicating whether each execution result message recorded in the local storage unit has been successfully sent and confirmed by the permission semantic adaptation gateway. It can be represented by status values ​​such as not sent, sent pending confirmation, and confirmed. The preset check cycle is the interval at which the local permission execution agent periodically checks unconfirmed execution result information in the local storage unit. It can be configured according to system load, network conditions, or importance level. Execution result information that has not yet been successfully confirmed by the permission semantic adaptation gateway refers to execution result records in the local storage unit whose sending status is marked as sent pending confirmation. Feedback waiting timer refers to the timer process initiated by the permission semantic adaptation gateway after distributing domain permission instructions, while waiting for the execution result feedback from the local permission execution agent. The preset timeout duration is the threshold time at which the permission semantic adaptation gateway determines that the feedback has timed out after the feedback waiting timer reaches this duration; it can be configured based on factors such as network latency and local system processing capabilities. Valid execution result feedback refers to the execution result information received by the permission semantic adaptation gateway that is correctly formatted and contains the necessary instruction identifiers and execution status information.The execution status is temporarily marked as pending. This means that after the permission semantic adaptation gateway times out, it temporarily marks the status of the domain permission instruction in the global permission view, indicating that its final execution result is still unclear and needs further confirmation.

[0054] This application's solution constructs a reliable execution result feedback channel by introducing local persistent storage and periodic retransmission mechanisms for execution result information on the local permission execution agent side, and a feedback waiting timer and timeout marking mechanism on the permission semantic adaptation gateway side. Specifically, after the local permission execution agent completes the execution of a received domain permission instruction, it immediately generates execution result information containing the instruction identifier, execution completion status, and execution completion timestamp, and stores this information in the local storage unit. Simultaneously, it attempts to send this information to the permission semantic adaptation gateway. The local storage unit records each execution result and its sending status as the basis for subsequent retransmissions. Even if the initial transmission fails due to network issues, the local permission execution agent will, according to a preset check cycle, traverse the execution result information marked as not yet successfully received and acknowledged by the permission semantic adaptation gateway in the local storage unit, and actively retransmit it. Meanwhile, the permission semantic adaptation gateway starts a feedback waiting timer after distributing the instruction. If no valid execution result feedback is received within the preset timeout period, the status of the instruction is temporarily marked as pending determination. Thanks to the local storage and retransmission capabilities of the local permission execution agent, and the timeout detection and status marking capabilities of the permission semantic adaptation gateway, even in the event of network instability or momentary interruption, the execution result information has a higher probability of ultimately reaching the permission semantic adaptation gateway. This reduces inconsistencies in permission states between the two ends due to lost feedback, ensuring the reliability of permission synchronization. This mechanism, combined with the basic process of the permission semantic adaptation gateway converting emergency permission objects into domain permission instructions based on emergency scenario information and sending them locally, forms a complete and fault-tolerant closed loop of permission control, from instruction generation and distribution to execution and feedback.

[0055] In some preferred embodiments, the local permission execution agent can be implemented as a daemon running on the target system server. This process receives domain permission instructions, such as permission change requests carried in JSON format, sent by the permission semantic adaptation gateway via a message queue. After successfully executing a locally executable operation, the daemon constructs an execution result information, also in JSON format, containing a unique identifier for the instruction, a boolean value indicating success or failure, and the execution completion time. This execution result information is immediately written to a local SQLite database file and marked as "not sent". The daemon then attempts to send this information to the permission semantic adaptation gateway via a network connection. If the transmission is successful and an acknowledgment response is received from the permission semantic adaptation gateway, the record is marked as "acknowledged" in the SQLite database. Simultaneously, the daemon starts a scheduled task, for example, every minute, to iterate through all execution result records marked "not sent" or "sent pending acknowledgment" in the SQLite database and attempt to resend them to the permission semantic adaptation gateway. On the permission semantic adaptation gateway side, when it sends an instruction to a local permission execution agent, it starts a 30-second timer for that instruction. If no execution result information containing the correct instruction identifier is received from the local permission execution agent within 30 seconds, the permission semantic adaptation gateway will mark the instruction as "pending determination" in its internal status record.

[0056] This application further proposes a method for receiving domain permission instructions, converting them into locally executable operations, and feeding back the execution results to a permission semantic adaptation gateway, which also includes:

[0057] When multiple consecutive instructions time out or the system load is low, for domain permission instructions with a status of pending determination, a status query request is proactively initiated to the corresponding local permission execution agent; the query request contains the unique identifier of the original domain permission instruction.

[0058] After receiving a status query request from the permission semantic adaptation gateway, the local permission execution agent retrieves the execution result information corresponding to the request instruction identifier from its local persistent storage unit and returns the retrieved information to the permission semantic adaptation gateway.

[0059] The permission semantic adaptation gateway updates the final execution status of the corresponding domain permission instructions maintained internally based on the execution result information actively fed back by the local permission execution agent or the execution result information obtained through active querying. This final execution status will be used to generate a global permission view and report it to the emergency command platform.

[0060] Among these, "multiple consecutive instruction feedback timeouts or low system load" refers to situations where the permission semantic adaptation gateway fails to receive valid feedback within a preset timeout period after sending a domain permission instruction to the local permission execution agent, and this occurs consecutively a preset number of times. Alternatively, the permission semantic adaptation gateway may detect that the resource utilization of the network or local system it is connected to is lower than a preset threshold. This can be achieved by monitoring network packet loss rate, latency, bandwidth utilization, or system CPU and memory utilization, etc., with the aim of identifying abnormal or idle states that may lead to the failure or inefficiency of the passive feedback mechanism. A domain permission instruction with a status of "pending determination" refers to a situation where the permission semantic adaptation gateway is distributing a domain permission instruction to the local permission execution agent. After a domain permission command is issued, a feedback waiting timer is initiated. If no valid execution result feedback is received from the local permission execution agent within the preset timeout period, the permission semantic adaptation gateway temporarily marks the execution status of the domain permission command as pending. This is to identify commands that require further confirmation of the actual execution result. Actively initiating a status query request to the corresponding local permission execution agent means that when specific triggering conditions are met (such as continuous timeouts or low load), the permission semantic adaptation gateway no longer waits for passive feedback from the local permission execution agent, but actively constructs and sends a query message to the specific local permission execution agent. This query message can use a query message format based on the unique identifier of the command. The purpose of this implementation is to overcome the limitations of passive feedback mechanisms and obtain instruction execution status in a timely manner. The local persistent storage unit refers to the storage medium used by the local permission execution agent to permanently store domain permission instruction execution results. This can be implemented using a database, file system, or dedicated persistent storage module. Its purpose is to ensure that the execution results can still be retrieved after the local permission execution agent restarts or malfunctions. Retrieving the execution results corresponding to the requested instruction identifier means that the local permission execution agent, based on the unique instruction identifier contained in the query request sent by the permission semantic adaptation gateway, searches for and retrieves the execution result record matching the identifier in its local persistent storage unit. It can be implemented using database query statements or file index lookup, with the aim of accurately obtaining the execution status of a specific instruction. Among them, updating the final execution status of the corresponding domain permission instruction maintained internally means that the permission semantic adaptation gateway corrects the execution status of the instruction recorded internally based on the execution result information obtained from the local permission execution agent (whether it is obtained through active feedback or active query), updating it from pending or other temporary status to the final success, failure, or partial success status. This can be implemented by modifying the data structure in memory or updating the database record, with the aim of ensuring that the permission semantic adaptation gateway's grasp of the instruction execution status is accurate and up-to-date.The final execution status refers to the final determination of the execution result of the domain permission command after confirmation by the permission semantic adaptation gateway. This can include states such as success, failure, partial success, and cancellation. Its purpose is to provide accurate basic data for generating a global permission view and reporting to the emergency command platform.

[0061] In some preferred embodiments, this application is implemented as follows: Assume an emergency command platform issues a domain permission instruction, requiring a local permission execution agent to perform a sensitive operation. The permission semantic adaptation gateway sends this instruction to the corresponding local permission execution agent. After the local permission execution agent executes the operation, it stores the execution result (e.g., success, failure, and related error codes) along with the instruction's unique identifier in its local SQLite database and attempts to send the result back to the permission semantic adaptation gateway via a message queue. If, due to network fluctuations or message queue congestion, the permission semantic adaptation gateway does not receive feedback on the instruction's execution result three consecutive times within a preset 10-second timeout period, the permission semantic adaptation gateway will mark the instruction's status as pending determination internally. Simultaneously, the permission semantic adaptation gateway continuously monitors the network connection status with the local permission execution agent, for example, through periodic pinging or monitoring TCP connection activity. If consecutive timeouts are detected, or if the current bandwidth utilization of the network link with the local permission execution agent is detected to be below 5%, the permission semantic adaptation gateway will trigger an active query process. The permission semantic adaptation gateway constructs a status query request message containing a unique identifier (e.g., a UUID) of the original domain permission instruction. The gateway sends this query request to the corresponding local permission execution agent via a separate, higher-priority communication channel (e.g., a dedicated RPC interface). Upon receiving the query request, the local permission execution agent immediately executes a query operation in its local SQLite database to find a record matching the UUID in the request. If a matching record is found, the agent encapsulates the execution result information (e.g., "execution successful" or "execution failed, error code: XXX") into a response message and sends it back to the permission semantic adaptation gateway via the aforementioned dedicated RPC interface. Upon receiving this execution result information obtained through the active query, the gateway uses this information to overwrite or confirm its internal status flag for the instruction. For example, if the query result is "execution successful," the gateway updates the final execution status of the instruction to "execution successful." This updated final execution status is then used to generate the latest global permission view and reported to the emergency command platform via an API interface, ensuring that the command platform can perform subsequent operations based on accurate permission status information.

[0062] In response, this application further proposes a step-by-step approach to adjust a preset threshold based on scenario evolution information and risk level information to obtain the adjusted threshold, including:

[0063] If the adjustment direction indicated by the scenario evolution information is inconsistent with the adjustment direction indicated by the risk level information, then the first adjustment intention formed by each scenario evolution factor contained in the scenario evolution information on the preset threshold, and the second adjustment intention formed by the risk level information on the preset threshold are obtained; both the first adjustment intention and the second adjustment intention include the adjustment trend and the adjustment magnitude.

[0064] Determine whether there is a conflict in adjustment trends among the primary adjustment intentions formed by the evolution factors of each scenario, and whether there is a conflict in adjustment trends between the adjustment intentions formed by the comprehensive information on scenario evolution and the adjustment intentions formed by the risk level information;

[0065] When it is determined that there is a conflict of adjustment trend, the conflict resolution logic in the pre-set emergency response strategy set is invoked to prioritize and integrate the conflicting adjustment intentions and output the dominant adjustment intention.

[0066] The net adjustment effect value is determined based on the dominant adjustment intention and the preset influence factors associated with each dominant adjustment intention;

[0067] The preset threshold is adjusted based on the net adjusted effect value to generate the adjusted threshold.

[0068] Among them, scenario evolution information refers to data or signals characterizing the dynamic changes of emergency scenarios, which can be implemented using time series data, state transition indicators, or trend indicators, and its purpose is to reflect changes in the emergency environment; risk level information refers to the risk assessment results associated with the type of authorized operation, which can be implemented using predefined risk levels (e.g., high, medium, low) or quantitative risk scores, and its purpose is to measure the potential risks that specific operations may bring; preset thresholds refer to reference values ​​used to assess the confidence of the authorization mapping strategy, which can be implemented using fixed values, statistical values ​​based on historical data, or values ​​calculated according to general rules, and their purpose is to set the judgment criteria for triggering manual review; adjustment direction refers to raising or lowering the preset thresholds. The decreasing trend indication can be implemented using Boolean values ​​(e.g., true for increase, false for decrease) or enumerated values ​​(e.g., "increase", "decrease"), aiming to indicate the trend of threshold change. Scene evolution factors refer to the specific elements constituting scene evolution information, which can be implemented using indicators such as disaster level, communication status, resource availability, or time progress, aiming to refine the composition of scene changes. The first adjustment intention refers to the adjustment tendency formed by each scene evolution factor on the preset threshold, which can be implemented using structured data containing adjustment trends and adjustment magnitudes, aiming to quantify the impact of individual scene factors on the threshold. The second adjustment intention refers to the adjustment tendency formed by risk level information on the preset threshold, which can be implemented using... Structured data containing adjustment trends and adjustment magnitudes is used to quantify the impact of risk levels on thresholds. Adjustment trend refers to the direction of threshold change indicated by the adjustment intention, which can be implemented using enumerated values ​​(e.g., "increase," "decrease") to clarify whether the adjustment increases or decreases the threshold. Adjustment magnitude refers to the magnitude of threshold change indicated by the adjustment intention, which can be implemented using numerical values ​​(e.g., percentages or absolute values) to quantify the degree of adjustment. Conflicting adjustment trends refer to two or more adjustment intentions indicating opposite adjustment trends, which can be implemented using logical judgments (e.g., one intention indicates an increase, another a decrease) to identify conflicts between adjustment signals. The emergency response strategy set refers to... The pre-defined set of rules for handling various situations in emergency scenarios can be implemented using rule bases, decision tables, or expert systems. Its purpose is to provide a standard process for handling complex situations. Conflict resolution logic refers to the algorithms or rules within the emergency response strategy set used to resolve conflicting adjustment intentions. It can be implemented using priority rules, weighted average algorithms, or scenario-matching-based decision trees. Its purpose is to determine the final adjustment direction and magnitude when conflicts occur. Priority determination and integration refers to the process of ranking conflicting adjustment intentions by importance and performing comprehensive processing based on the conflict resolution logic. It can be implemented using rule matching, scoring calculation, or decision tree traversal. Its purpose is to derive a consistent adjustment conclusion from conflicting intentions.The dominant adjustment intention refers to the adjustment intention or its combined result that is determined to have a decisive influence after conflict resolution. It can be achieved through a single adjustment intention, a combination of multiple adjustment intentions, or a new comprehensive intention, and its purpose is to serve as the basis for subsequently determining the net adjustment effect value. The pre-set influence factor refers to the weight associated with the dominant adjustment intention, used to quantify its contribution to the net adjustment effect value. It can be implemented using pre-set values, and its purpose is to reflect the importance of different dominant intentions. The net adjustment effect value refers to the final threshold adjustment amount calculated after comprehensively considering all dominant adjustment intentions and their influence factors. It can be implemented using weighted summation or more complex calculation models, and its purpose is to determine the actual adjustment value of the pre-set threshold.

[0069] In some preferred embodiments, for example, suppose that when evaluating the confidence level of a mapping strategy for a high-risk permission operation (e.g., a large fund transfer), the initial preset threshold is 0.6. The currently calculated confidence level is 0.55. At this point, the system obtains scenario evolution information and risk level information. Scenario evolution information may include two factors: the degree of communication network congestion (factor 1) and the disaster level (factor 2). The risk level information indicates that the operation is high-risk. Analysis reveals that an increase in the degree of communication network congestion (factor 1) may indicate that the system state is unstable and tends to lower the threshold (e.g., a first adjustment intention). Figure 1 The threshold tends to decrease (by an order of magnitude of 0.05) to make it easier to trigger manual review when uncertainty increases. An increased disaster severity level (Factor 2) may indicate an urgent situation requiring a rapid response, thus tending to lower the threshold (e.g., the first adjustment intention). Figure 2The system initially tends to lower the threshold (by a factor of 0.1) to reduce the triggering of manual review. However, high-risk level information strongly indicates the need for caution and tends to raise the threshold (e.g., second adjustment intention: tends to raise, by a factor of 0.2) to ensure that high-risk operations are fully reviewed. In this case, the overall scenario evolution information tends to lower the threshold, while the risk level information tends to raise the threshold, resulting in inconsistent adjustment directions. The system determines that there is no conflict in adjustment trends between the first adjustment intentions formed by the various scenario evolution factors (factor 1 and factor 2) (both tend to lower), but there is a conflict in adjustment trends between the adjustment intention formed by the overall scenario evolution information (tends to lower) and the adjustment intention formed by the risk level information (tends to raise). When a conflict is determined, the system invokes the conflict resolution logic within the pre-set emergency response strategy set. This logic may determine the priority of emergency objectives based on the current emergency scenario (e.g., high-risk operations in an environment of escalating disaster and poor communication), for example, prioritizing "ensuring fund security" over "improving response speed." Based on this priority, the conflict resolution logic prioritizes and integrates the intentions to lower and raise the threshold. For example, the logic might stipulate that in high-risk scenarios, the intention to adjust the risk level has higher priority, or a weighted average might be used, but with a higher weight given to the risk level. After priority determination and integration, the dominant adjustment intention is output. For example, the dominant adjustment intention might comprehensively consider high risk (increase by 0.2) and disaster escalation (decrease by 0.1), resulting in a net effect of an increase of 0.1. Alternatively, if the risk priority is extremely high, the dominant intention directly adopts the intention of the risk level (increase by 0.2). Assuming the final determined dominant adjustment intention is to increase the threshold, the net adjustment effect value is 0.15 (this is a comprehensive calculation result, considering the dominant intention and influencing factors). Based on the net adjustment effect value of 0.15, the preset threshold is adjusted to 0.6, resulting in an adjusted threshold of 0.6 + 0.15 = 0.75. Finally, the calculated confidence level of 0.55 is compared with the adjusted threshold of 0.75. Since 0.55 is lower than 0.75, the system triggers a manual review process to confirm or correct the permission mapping strategy.

[0070] Through the above technical solution, this application can effectively identify and resolve potential conflicts between scenario evolution information and risk level information when adjusting preset thresholds, avoiding inaccurate threshold adjustments caused by simply handling conflicts. This makes confidence assessments based on the adjusted thresholds more reliable, improves the accuracy of triggering manual review decisions, and thus ensures the effectiveness and security of multi-level access control between banks, government, and enterprises in dynamically changing emergency scenarios.

[0071] In response, this application further proposes that when a conflict is determined to exist in relation to adjustment trends, the following steps are taken: The conflict resolution logic within a pre-defined set of emergency response strategies is invoked to prioritize and integrate conflicting adjustment intentions, and then the dominant adjustment intention is output.

[0072] Determine the degree of match between the current combination of conflicting adjustment intentions and the conflict resolution rules within the pre-set emergency response strategy set;

[0073] Determine the priority of emergency targets corresponding to the current emergency scenario information based on the degree of matching;

[0074] Based on the priority of emergency objectives, adjust the priority determination parameters of the conflict resolution rules in the preset emergency response strategy set or select the backup resolution rules in the preset emergency response strategy set that are suitable for the current emergency objectives, so as to form an adaptive conflict resolution configuration for the conflicting combination of the current adjustment intention.

[0075] Based on the adaptive conflict resolution configuration, conflicting adjustment intentions are prioritized and integrated, and the dominant adjustment intention is output.

[0076] This application's solution, when determining a conflict with an adjustment tendency, no longer uses a fixed resolution method, but instead invokes conflict resolution logic from a pre-set emergency response strategy set. First, the system analyzes the specific combinations of the current conflicting adjustment intentions and matches them against a pre-set conflict resolution rule library to find the most relevant rule. Simultaneously, combined with current emergency scenario information, the system dynamically determines the most important emergency objective at the current stage. Based on this emergency objective priority, the system flexibly adjusts the internal parameters of the matched conflict resolution rules, or directly selects a more suitable backup resolution rule to replace the default rule. In this way, an adaptive conflict resolution configuration is formed for the specific conflict and emergency scenario. Finally, the system applies this adaptive configuration to prioritize and integrate the conflict adjustment intentions, thereby deriving a dominant threshold adjustment intention that best serves the current emergency objective. This dominant intention will be used for subsequent threshold calculations. This dynamic adjustment of the resolution strategy makes threshold adjustments less rigid, more accurately reflecting the actual needs in complex emergency scenarios, and improving the accuracy and reliability of the permission mapping strategy confidence assessment. Based on identifying conflicts with a tendency to adjust and obtaining each adjustment intention, this solution provides the ability to intelligently adjust thresholds in complex conflict situations, enhancing the robustness and adaptability of the entire access control method.

[0077] In some preferred embodiments, for example, suppose that in a flood disaster, the initial emergency objective is "rapid rescue," which later shifts to "post-disaster recovery and prevention of secondary disasters." The scenario evolution information may initially indicate "rapid spread of the disaster," leading to an intention to lower the threshold to expedite permission approval; later, it may indicate "slow decline in water level," leading to an intention to raise the threshold to strengthen risk control. Simultaneously, a high-risk operation (such as large-scale fund disbursement) consistently leads to an intention to raise the threshold. In the early stages of the disaster, the scenario evolution (lowering the threshold) conflicts with the high-risk operation (raising the threshold). The system determines that the intention to lower the threshold due to "rapid spread of the disaster" conflicts with the intention to raise the threshold due to "high-risk fund disbursement." The system identifies the current conflicting combination as "rapid scenario deterioration vs. high-risk operation" and finds a matching rule in the preset strategy set, such as "Rule A: Handling the conflict between scenario deterioration and high-risk operation." Based on the current emergency scenario information (early stage of the disaster, emergency objective is rapid rescue), the system determines that the "rapid rescue" objective has the highest priority. Based on the priority of the "rapid rescue" objective, the system adjusts the priority judgment parameters of Rule A. For example, it temporarily increases the weight of scenario evolution factors, or selects the backup rule "Rule B: Rapid Response Priority Resolution Rule," which assigns a higher priority to the scenario evolution intent, forming an adaptive configuration. Applying the adaptive configuration, the system determines that the intent to lower the threshold in scenario evolution is the dominant intent and outputs the final dominant adjustment intent based on its magnitude. During the post-disaster recovery period, suppose the scenario evolution (water level drop, threshold increase) conflicts with another intent to lower the threshold (such as resource conservation). The system determines that the threshold increase intent caused by "slow water level drop" conflicts with the threshold decrease intent caused by "resource conservation." The system identifies the current conflicting combination as "post-disaster recovery vs. resource conservation," finds a matching rule, such as "Rule C: Handling Multi-Factor Conflicts in the Recovery Period." Based on the current emergency scenario information (post-disaster recovery period, emergency objectives are post-disaster recovery and prevention of secondary disasters), the system determines that the objectives of "fund security" and "effective resource utilization" have higher priorities. Based on the priority of the objectives, the system adjusts the parameters of rule C, for example, by increasing the weight of resource utilization factors, or by selecting the alternative rule "Rule D: Risk Control and Resource Optimization Mitigation Rule," thus forming an adaptive configuration. Applying this adaptive configuration, the system may determine that the resource-saving intention is the dominant intention and output a comprehensive dominant adjustment intention.

[0078] In response, this application further proposes a domain-specific mapping rule management process; the domain-specific mapping rule management process includes:

[0079] When a specific domain mapping rule is submitted after editing or when a new specific domain mapping rule is added, the system checks whether there are any configuration-level conflicts or inconsistencies between the newly submitted content and other existing rules in the rule base, based on pre-configured logical judgment rules, and outputs the detection results. The logical judgment rules include the degree of overlap of the rule application conditions, the mutual exclusivity of permission operations, and the dependency relationship of the order of rule execution.

[0080] Among them, the specific domain mapping rule management step refers to the process of lifecycle management of specific domain mapping rules used to convert emergency permission objects into domain permission instructions, which may include rule creation, editing, deletion, storage and verification;

[0081] Among them, logical judgment rules refer to a set of pre-configured judgment criteria used to evaluate whether there are conflicts or inconsistencies between mapping rules in a specific domain. These rules can be implemented using logical reasoning based on rule engines or dependency analysis based on graph models.

[0082] Among them, the overlap of the applicable conditions of the rules refers to assessing whether there is an intersection between the effective condition sets defined by two or more specific domain mapping rules. Its purpose is to identify situations that may cause the same emergency permission object to be matched by multiple rules at the same time and produce different conversion results.

[0083] Among them, the mutual exclusivity of permission operations refers to evaluating whether the operations contained in the domain permission instructions defined by two or more specific domain mapping rules are semantically mutually exclusive. Its purpose is to identify situations that may lead to the simultaneous issuance of allow and deny instructions for the same target resource or operation.

[0084] Among them, the sequential dependency of rule execution refers to assessing whether there is a dependency on the execution order between mapping rules in a specific domain. That is, whether the correct execution or effectiveness of a certain rule is premised on the execution or effectiveness of one or more previous rules. Its purpose is to identify situations that may lead to a break in the rule chain or incorrect execution results.

[0085] This application's solution introduces a validation mechanism for the rules themselves, building upon the fact that permission conversion relies on specific domain mapping rules. When a new or modified rule is submitted, it is not directly added to the database and takes effect; instead, it is first checked through logical rule evaluation. This validation process examines whether the new rule conflicts with existing rules in terms of applicable conditions, operational content, and execution order. This pre-emptive validation can detect and prevent potential misconfigurations before the rule takes effect. Unlike existing solutions that rely solely on manual management or simple validation, this provides an automated, multi-dimensional conflict detection capability. This capability ensures the internal consistency and accuracy of the rule base, thereby guaranteeing the reliability of subsequent permission conversions. This systematic validation of rules before use effectively avoids permission conversion errors caused by rule conflicts or inconsistencies, improves the accuracy of domain permission instructions, and ultimately enhances the efficiency and reliability of the entire emergency response process.

[0086] In some preferred embodiments, the domain-specific mapping rule management steps can be implemented as follows: When the system receives a new domain-specific mapping rule submitted by the administrator through the management interface, the system immediately initiates a rule detection process. First, the system analyzes the new rule based on a pre-configured set of logical judgment rules. For example, regarding the overlap of rule application conditions, the system can traverse all existing rules in the rule base and compare the application conditions defined by the new rule (such as "flood disaster," "enterprise user," and "material reporting") with the application conditions of existing rules. If the conditions of the new rule overlap with the conditions of an existing rule, the system will mark this potential overlap. Next, the system checks the mutual exclusion of permission operations. For example, if the new rule allows "enterprise users" to "report materials" in a "flood disaster" scenario, while a rule in the rule base already prohibits "enterprise users" from "reporting materials" in any "disaster" scenario, the system will mark this operation as mutually exclusive. Simultaneously, the system checks the dependencies between rule execution sequences. For example, if a new rule's activation requires a specific type of emergency response to be initiated, the system verifies the existence of a rule defining that activation condition and checks the validity of the dependency chain. After completing the checks on all logical judgment rules, the system generates a detailed report indicating all conflicts or inconsistencies found and outputs the report to the administrator. If conflicts exist, the system can prevent the new rule from being saved or activated until the administrator corrects it based on the report.

[0087] This application further proposes that the data structure of the emergency permission object be defined using an extensible markup language or JSON format.

[0088] Emergency permission objects refer to data carriers used to carry permission-related information that needs to be transmitted and processed across systems in emergency scenarios. They include standard permission information and emergency scenario information, and their purpose is to encapsulate permission instructions and related emergency context.

[0089] Extensible markup language (EXPLAIN) is a markup language used to encode documents. It can use a tree structure to represent data, supports custom tags, and aims to provide a structured and extensible way of describing data.

[0090] JSON is a lightweight data exchange format that uses a combination of key-value pairs and arrays to represent data. Its purpose is to provide a concise and easy-to-parse way of describing data.

[0091] In some preferred embodiments, emergency permission objects can be defined in JSON format. For example, an emergency permission object for granting Enterprise D the permission to report specific materials can be represented as a JSON object containing key-value pairs, such as "permissionType":"material report", "targetEntity":"Enterprise D", "entityId":"D1", "materialType":"lifeboat", "validityPeriod":"24h", "emergencyLevel":"Level I". Alternatively, it can be defined in XML format, which can be a root element. <emergencypermission>`, containing child elements` <standardpermission>`and` <emergencyscenario> `，` <standardpermission>Below is <type> Material reporting< / type> `、` <target> Enterprise Ding< / target> ` and other elements,` <emergencyscenario>Below is <material> lifeboat< / material> `、` <duration> 24h< / duration> Elements such as `. These specific format definitions enable the permission semantic adaptation gateway to accurately extract information such as permission type, target entity, material type, validity period, and emergency level according to preset JSON or XML parsing rules, and then perform subsequent permission mapping and instruction conversion.

[0092] The above technical solution utilizes an extensible markup language or JSON format to define the data structure of emergency permission objects, ensuring seamless transmission and parsing of these objects across heterogeneous systems of banks, government agencies, and enterprises. This avoids permission configuration errors or delays caused by incompatible data formats. Furthermore, this data structure offers excellent scalability, allowing for the easy addition of new attributes and fields to emergency permission objects to meet evolving permission management needs without modifying the existing system architecture.

[0093] In some of the embodiments described above in this application, a multi-level access control method for banks, government, and enterprises is proposed. Specifically, this method may include constructing an emergency access object and sending it to an access semantic adaptation gateway. The access semantic adaptation gateway selects an access mapping strategy based on emergency scenario information and converts it into domain access instructions. It also receives domain access instructions, converts them into locally executable operations, and provides feedback on the execution results. This enables rapid configuration and management of emergency access across organizations. However, in its implementation, only the method steps are proposed, and there is a lack of a corresponding system to implement the above method, which makes it impossible to implement the method and verify its feasibility and effectiveness.

[0094] In response, this application further proposes a multi-level access control system for banks, government, and enterprises, such as... Figure 2 As shown, the system includes:

[0095] Module 201 is used to construct emergency permission objects and send them to the permission semantic adaptation gateway. The emergency permission object includes standard permission information and emergency scenario information. The permission semantic adaptation gateway is deployed in the access layer of participating institutions such as banks, governments and enterprises to receive and parse the emergency permission objects.

[0096] The conversion module 202 is used to select a preset permission mapping strategy based on the emergency scenario information and the permission semantic adaptation gateway, and convert the emergency permission object into a domain permission instruction according to the permission mapping strategy and the specific domain mapping rules, and send the domain permission instruction to the local machine; the domain permission instruction is a permission instruction applicable to banks, government and enterprises.

[0097] The execution module 203 is used to receive domain permission instructions and convert them into locally executable operations, and to feed back the execution results to the permission semantic adaptation gateway.

[0098] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.< / emergencyscenario> < / standardpermission> < / emergencyscenario> < / standardpermission> < / emergencypermission>

Claims

1. A method for multi-level access control between banks, government, and enterprises, characterized in that, include: An emergency permission object is constructed and sent to the permission semantic adaptation gateway; the emergency permission object includes standard permission information and emergency scenario information; the permission semantic adaptation gateway is deployed in the access layer of participating institutions (banks, government, and enterprises) to receive and parse the emergency permission object. Based on the emergency scenario information, the permission semantic adaptation gateway selects a preset permission mapping strategy, and converts the emergency permission object into a domain permission instruction according to the permission mapping strategy and specific domain mapping rules, and sends the domain permission instruction to the local machine; the domain permission instruction is a permission instruction applicable to banks, government and enterprises. Receive the domain permission instructions and convert them into locally executable operations, and feed back the execution results to the permission semantic adaptation gateway; The emergency scenario information includes emergency parameters; the step of selecting a preset permission mapping strategy by the permission semantic adaptation gateway based on the emergency scenario information includes: The emergency scenario information is verified for completeness, and the emergency parameters after completeness verification are semantically analyzed and standardized based on a preset emergency parameter semantic library. The system detects whether there are any conflicts among the standardized emergency parameters. If there are conflicts, the conflicting parameters are adjudicated according to the preset priority rules to obtain the final emergency parameters. Based on the final emergency parameters, select or adjust the permission mapping strategy; Assess the confidence level of the permission mapping strategy selected or adjusted based on the final emergency parameters. If the confidence level is lower than a preset threshold, trigger a manual review process to confirm or correct the permission mapping strategy.

2. The method for multi-level access control between banks, government, and enterprises according to claim 1, characterized in that, Assess the confidence level of the permission mapping strategy selected or adjusted based on the final emergency parameters. If the confidence level is lower than a preset threshold, trigger a manual review process to confirm or correct the permission mapping strategy, including: Based on the final emergency parameters, the confidence level of the selected or adjusted permission mapping strategy is evaluated to obtain the confidence level; Obtain scenario evolution information that characterizes the dynamic evolution of emergency scenarios, as well as risk level information of permission operation types associated with the selected or adjusted permission mapping strategy; Based on the scenario evolution information and the risk level information, the preset threshold is adjusted to obtain the adjusted threshold; If the confidence level is lower than the adjusted threshold, the manual review process is triggered to confirm or correct the permission mapping strategy.

3. The method for multi-level access control between banks, government, and enterprises according to claim 1, characterized in that, The locally executable operation is executed based on a local permission execution proxy; receiving the domain permission instruction, converting it into a locally executable operation, and feeding back the execution result to the permission semantic adaptation gateway includes: After executing the domain permission instruction received from the permission semantic adaptation gateway, the local permission execution agent generates execution result information containing the instruction identifier, execution completion status, and execution completion timestamp of the domain permission instruction; the local permission execution agent stores the execution result information in the local storage unit and sends it to the permission semantic adaptation gateway; the local storage unit records each execution result information and its sending status; The local permission execution agent, according to a preset check cycle, traverses the execution result information recorded in the local storage unit that has not yet been successfully received and confirmed by the permission semantic adaptation gateway, and resends it to the permission semantic adaptation gateway. After distributing a domain permission instruction to the local permission execution agent, the permission semantic adaptation gateway starts a feedback waiting timer for that instruction. If no valid execution result feedback is received from the local permission execution agent within the preset timeout period, the permission semantic adaptation gateway temporarily marks the execution status of the domain permission instruction as pending.

4. The method for multi-level access control between banks, government, and enterprises according to claim 3, characterized in that, The step of receiving the domain permission instruction, converting it into a locally executable operation, and feeding back the execution result to the permission semantic adaptation gateway also includes: When multiple consecutive instruction feedback timeouts occur or the system load is low, for domain permission instructions with a status of pending determination, a status query request is proactively initiated to the corresponding local permission execution agent; the query request contains the unique identifier of the original domain permission instruction. After receiving a status query request from the permission semantic adaptation gateway, the local permission execution agent retrieves the execution result information corresponding to the unique identifier in the query request from its local persistent storage unit, and returns the retrieved information to the permission semantic adaptation gateway. The permission semantic adaptation gateway updates the final execution status of the corresponding domain permission instructions maintained internally based on the execution result information actively fed back by the local permission execution agent or the execution result information obtained through active querying; the final execution status will be used to generate a global permission view and report it to the emergency command platform.

5. The method for multi-level access control between banks, government, and enterprises according to claim 2, characterized in that, Based on the scenario evolution information and the risk level information, the preset threshold is adjusted to obtain the adjusted threshold, including: If the adjustment direction indicated by the scenario evolution information is inconsistent with the adjustment direction indicated by the risk level information, then the first adjustment intention formed by each scenario evolution factor included in the scenario evolution information on the preset threshold, and the second adjustment intention formed by the risk level information on the preset threshold are obtained; the first adjustment intention and the second adjustment intention both include the adjustment trend and the adjustment magnitude. Determine whether there is a conflict in adjustment trends among the first adjustment intentions formed by the various scenario evolution factors, and whether there is a conflict in adjustment trends between the adjustment intentions formed by the comprehensive scenario evolution information and the adjustment intentions formed by the risk level information; When it is determined that there is a conflict of adjustment trend, the conflict resolution logic in the pre-set emergency response strategy set is invoked to prioritize and integrate the conflicting adjustment intentions and output the dominant adjustment intention. Based on the dominant adjustment intentions and the preset influence factors associated with each dominant adjustment intention, the net adjustment effect value is determined; The preset threshold is adjusted based on the net adjusted effect value to generate the adjusted threshold.

6. The method for multi-level access control between banks, government, and enterprises according to claim 5, characterized in that, When a conflict is identified as a potential adjustment, the conflict resolution logic within the pre-defined emergency response strategy set is invoked to prioritize and integrate the conflicting adjustment intentions, outputting the dominant adjustment intention, including: Determine the degree of match between the current combination of conflicting adjustment intentions and the conflict resolution rules within the preset emergency response strategy set; The priority of emergency targets corresponding to the current emergency scenario information is determined based on the degree of matching. Based on the priority of the emergency target, adjust the priority determination parameters of the conflict resolution rules in the preset emergency response strategy set or select the backup resolution rules in the preset emergency response strategy set that are suitable for the current emergency target, so as to form an adaptive conflict resolution configuration for the conflicting combination of the current adjustment intention. Based on the aforementioned adaptive conflict resolution configuration, conflicting adjustment intentions are prioritized and integrated, and a dominant adjustment intention is output.

7. The method for multi-level access control between banks, government, and enterprises according to claim 1, characterized in that, The method also includes a domain-specific mapping rule management step; The specific domain mapping rule management steps include: In response to the submission of an edited or newly added domain-specific mapping rule, the system detects whether there are configuration-level conflicts or inconsistencies between the newly submitted content and other existing rules in the rule base, based on pre-configured logical judgment rules, and outputs the detection results. The logical judgment rules include the overlap of rule application conditions, the mutual exclusivity of permission operations, and the sequential dependency of rule execution.

8. A multi-level access control method for banks, government, and enterprises according to any one of claims 1-7, characterized in that, The data structure of the emergency permission object is defined using an extensible markup language or JSON format.

9. A multi-level access control system for banks, government, and enterprises, characterized in that, include: A construction module is used to construct emergency permission objects and send the emergency permission objects to the permission semantic adaptation gateway; the emergency permission objects include standard permission information and emergency scenario information; the permission semantic adaptation gateway is deployed in the access layer of participating institutions such as banks, governments and enterprises, and is used to receive and parse the emergency permission objects; The conversion module is used to select a preset permission mapping strategy from the permission semantic adaptation gateway based on the emergency scenario information, and convert the emergency permission object into a domain permission instruction based on the permission mapping strategy and a specific domain mapping rule, and send the domain permission instruction to the local machine; the domain permission instruction is a permission instruction applicable to banks, government and enterprises. The execution module is used to receive the domain permission instructions, convert them into locally executable operations, and feed back the execution results to the permission semantic adaptation gateway. The emergency scenario information includes emergency parameters; the step of selecting a preset permission mapping strategy by the permission semantic adaptation gateway based on the emergency scenario information includes: The emergency scenario information is verified for completeness, and the emergency parameters after completeness verification are semantically analyzed and standardized based on a preset emergency parameter semantic library. The system detects whether there are any conflicts among the standardized emergency parameters. If there are conflicts, the conflicting parameters are adjudicated according to the preset priority rules to obtain the final emergency parameters. Based on the final emergency parameters, select or adjust the permission mapping strategy; Assess the confidence level of the permission mapping strategy selected or adjusted based on the final emergency parameters. If the confidence level is lower than a preset threshold, trigger a manual review process to confirm or correct the permission mapping strategy.

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