170 results about "Validation rule" patented technology

The invention provides a low-code dynamic configuration method based on a natural language, and relates to the technical field of natural language processing, and the method comprises the steps: carrying out semantic analysis on a natural language description input by a user through an intelligent agent, extracting a page type, a field attribute, a verification rule and interaction logic, and generating structured configuration data; dynamically generating JSON metadata for describing page layout, field components, verification rules and interaction logic according to a preset template on the basis of the structured configuration data; according to page function requirements, interface metadata matched with the JSON metadata is generated, and the interface metadata comprises a request address, a parameter list and corresponding SQL (Structured Query Language) operation logic; and analyzing the JSON metadata by utilizing a low-code configuration rendering engine, dynamically generating an interactive management function page, and modifying the JSON metadata in real time and re-rendering the page through natural language interaction between a user and an intelligent agent.

The invention discloses a data processing method and system based on a bidding and tendering management platform. The method comprises the following steps: obtaining a bidding and tendering data set and constructing an initial supplier set; dynamically screening the initial supplier set based on a preset qualification verification rule to generate a compliance supplier set; performing multi-dimensional semantic analysis on bidding document contents in the compliance supplier set to generate a risk assessment report; and generating a recommended supplier sequence based on the risk assessment report and the bid invitation party demand information. The method has the following advantages and effects: semantic mapping and dynamic weight distribution among data are realized; based on dynamic rules and real-time data updating, response delay caused by manual intervention is reduced; through confidence scoring, a quotation rationality model and performance matching degree calculation, a quantifiable risk assessment report is generated, and subjective deviation is reduced; and the recommendation logic is dynamically adjusted in combination with the customized demand of the bid invitation party, and the intelligent level and the result credibility of the bid invitation and tendering process are improved.

The invention provides an API behavior prediction and security policy management and control method based on machine learning, and relates to the field of computer network security, and the method comprises the steps: obtaining API original data in real time, preprocessing the original data, obtaining the preprocessed original data, obtaining API dimension features in real time based on the preprocessed original data, and fusing the API dimension features to obtain unstructured data, establishing a dynamic feature validity verification rule to pre-process the unstructured data to obtain a standardized feature tensor of a unified dimension; joint modeling of API behavior spatio-temporal characteristics is carried out through a collaborative architecture of a multi-head time attention mechanism and a dynamic graph neural network, API behavior prediction is carried out, an API dynamic security management and control strategy is generated in real time through a strategy engine, strategy execution is carried out, a security strategy execution effect is monitored in real time, and iterative optimization is carried out. According to the invention, the problems that the security control strategy of the traditional API gateway is fixed and rigid, and the security strategy is difficult to dynamically adjust according to the real-time access condition and behavior are solved.

Various aspects of the disclosure relate to automated testing for application programming interfaces (APIs). A dynamic API validation computing system leverages a generative AI model to dynamically generate a multitude of data sets and rules for use during API validation activities. A federated byzantine agreement mechanism performs the validation of each API using the generated test cases and test data. A generator engine incorporates a generative AI model that may be trained on a large corpus of API metadata and / or data characteristics to predict data patterns and / or validation rules for each of the APIs under test. The generator engine may also predict a structure and format of requests based on the training model inputs. Multiple Test cases for an API created through use of the generative AI model may be distributed and executed on different testing nodes that reach a consensus about whether each API has passed or failed.

The invention provides a business rule automatic processing method and system based on natural language understanding. The method comprises the following steps: extracting text content from an original document containing business rules and preprocessing the text content; utilizing a BERT-based metadata extraction model to extract structured metadata from the preprocessed text content; confirming and perfecting the structured metadata; on the basis of the confirmed metadata, a rule execution flow chart and / or a test case are / is automatically generated and used for verifying the correctness of rule logic; and according to the target format, converting the verified rule into a corresponding symbolic representation through a template engine to obtain a defined rule. According to the invention, the automatic conversion of the business rule from the natural language description to the symbolized executable form is realized, so that business personnel can directly use the natural language to define and maintain the business rule, the manual conversion cost is reduced, and the accuracy and efficiency of rule processing are improved.

The invention discloses a permission verification method and system applied to OA examination and approval, and relates to the technical field of permission verification, and the method comprises the steps: receiving an examination and approval request triggered by an OA system, carrying out the extraction according to the examination and approval request, and obtaining user identity information and an examination and approval content label set; triggering a multi-level permission verification mechanism based on the user identity information, and generating a dynamic verification rule set; performing permission verification on the approval content label according to the dynamic verification rule set, and formulating a target verification rule; and executing the target verification rule to perform multi-level cross verification on the user permission, generating a permission verification report according to a verification result, and feeding back the permission verification report to the OA system to trigger a subsequent approval process. The technical problems of low approval process efficiency and inaccurate authority control caused by fixed static rule configuration in the authority verification process in the prior art are solved, and the technical effects of improving the authority verification flexibility and accuracy and enhancing the approval process safety and intelligent level are achieved.

The invention discloses a business filling scene data acquisition method and system, a storage medium and electronic equipment, and the method comprises the steps: firstly storing filling historical data and domain knowledge into a vector database, and according to the current input of a user, searching related information, and combining the current input to generate a filling suggestion through a generation type large model; multi-modal information of the multi-end filling system is obtained, semantic understanding and information extraction are completed through a large model, and the multi-modal information is converted into structured data; mapping the structured data to a specified field by means of a field mapping rule; a data verification rule is designed, data verification is corrected through a rule engine or large model dynamic logic verification, and a verification result and a prompt suggestion are output; and finally, storing the processed and verified data, and providing data support for the user. According to the invention, the data acquisition efficiency is improved; the intention of the user can be predicted, corresponding suggestions can be provided, and the legality and accuracy of data are ensured.

The invention belongs to the technical field of cross-data island consensus, and particularly relates to a cross-data island consensus verification method and system based on credibility scoring. According to the invention, by dynamically evaluating the trust degree of each data island and combining network state fluctuation, real-time verification and abnormal early warning of a consensus result are realized, the stability and safety of cross-data island cooperation are effectively improved, the data consistency is ensured, the data risk caused by network fluctuation is reduced, the self-adaptive capability of the system is enhanced, and the method is suitable for large-scale popularization and application. In the consensus process, historical interaction events and a current cooperation state of a data island are considered, efficient alignment of cross-island features is achieved through a gradient exchange mechanism, a standardized consensus data view is generated, in addition, self-adaptive adjustment of a consensus verification rule is ensured by pre-deploying a trusted execution environment, and the consensus verification efficiency is improved. And the consensus accuracy and efficiency are further improved.

Computer-implemented system for real-time validation and threat mitigation for structured health transactions, including: a client policy repository that contains client-specific validation rules, consent restrictions, and risk thresholds; a trusted policy execution enclave that only allows policies and models after remote attestation of code and configuration, and decrypts and processes protected fields exclusively within the enclave; a grammatically aware streaming validator that enforces format and semantic constraints and synthesizes an auto-repair suggestion in case of parser errors, transforming inputs into a policy-compliant form with minimal changes; a hybrid risk engine that calculates rule-based and learned risk scores and furthermore evaluates a subset of features using data protection-preserving calculations to determine risk contributions without decoding selected fields; a causal graph generator that correlates related transactions over time into an entity-resolved, time-aligned graph and identifies impossibility patterns with edge-wise responsibility values; a coordinator for federated learning who updates models from client-local aggregates under differential privacy budgets and suspends aggregation when a distribution drift above a policy threshold is detected; an audit subsystem that generates zero-knowledge evidence demonstrating that selected compliance predicates for a transaction have been met without disclosing protected health information; a risk-adaptive flow control system that directs high-risk substreams into micro-quarantine sections with enhanced testing while maintaining the basic service quality for low-risk substreams; and a register that stores a validity context mark which links each decision to the identity of the policies, models, scope of consent and runtime environment used.

The invention discloses a multi-terminal detection score offset correction method and system, particularly relates to the field of financial risk control, is used for solving the problem of steady-state offset generated in the merging process of multi-terminal detection scores, and comprises the following steps: receiving cross-terminal original behaviors and collecting metadata under unified time reference and unified field specifications; the method comprises the following steps: extracting a terminal fingerprint table according to a sampling beat, a sensing path, a rendering mode and a quantification strategy, generating a time alignment table, dividing a stable fragment, a change fragment and a transition fragment by taking the terminal fingerprint table and the time alignment table as conditions, and constructing a segmented order-preserving mapping relation table; a cross-terminal consistency constraint graph is generated based on the segmented order-preserving mapping relation table to form a correction rule set, rules are verified in an offline playback window, a micro-correction list is output, and the correction rule set and the micro-correction list are read in the online merging stage to execute correction and output a unified scale score. And meanwhile, generating a feedback abstract, submitting, filing and publishing a version.

The invention discloses an intelligent extraction method and equipment for structural data of a scanned copy and a medium, and relates to the cross technical field of computer vision and intelligent document processing. The method comprises the following steps: acquiring a to-be-processed scanned copy image, and performing joint feature extraction on the scanned copy image based on a preset multi-modal neural network model to generate intermediate feature representation; constructing an extensible structured index template library containing field rules, value domain constraints and cross-field verification logic; based on an attention mechanism, performing intelligent semantic matching and mapping on the intermediate feature representation and a target field in an extensible structured index template library to output preliminary structured data; based on a verification rule preset in an extensible structured index template library, executing automatic logic verification and conflict resolution on the preliminary structured data to generate standard structured data conforming to business specifications; and carrying out serialization output on the standard structured data according to a predetermined format.

Systems and methods use dynamically generated validation rules. These validation rules comprise a first validation rule portion that is generated using a standardized validation process (e.g., corresponding to a standardized schema) and a second validation rule portion that is generated using a validation process selected based on a non-standardized schema that is specific to a respective asset type of the plurality of respective asset types.

A data processing system and method, and a related device, relating to the technical field of artificial intelligence (AI). The data processing system comprises a general-purpose processor and an AI accelerator card. The general-purpose processor is used for sending an operation request comprising authorization authentication information and requesting to process an AI model deployed in the AI accelerator card. The AI accelerator card is constructed to be provided with a trusted execution environment (TEE), and the AI accelerator card is used for running a policy enforcement point (PEP) component deployed in the TEE, and is further used for receiving the operation request and determining whether the authorization authentication information in the operation request complies with a verification rule in the PEP component, and when the authorization authentication information complies with the verification rule, the first operation request is executed to execute a processing operation on the AI model. In this way, the PEP component is deployed in the TEE of the AI accelerator card, that is, the PEP is deployed in an execution environment closer to the AI model, so that the AI model can be effectively prevented from being illegitimately accessed by the general-purpose processor, thereby ensuring access safety of the AI model in the AI accelerator card.

The invention belongs to the field of medical data processing. The invention provides a multi-modal data verification system and method in medical scientific research. The method comprises the following steps: extracting multi-modal data from different storage media; respectively analyzing and processing the extracted multi-modal data, respectively establishing a feature data model of each modal data and establishing a feature index; mapping the feature data models of the modal data to a unified vector space, performing data fusion according to the relationship of feature indexes of the feature data models, and generating and storing a wide model with multi-dimensional indexes; and according to a verification rule in a data processing process, slicing the wide model according to the feature index, and extracting a data feature information part corresponding to the verification rule to complete data verification. The method has the beneficial effects that all data of different modalities are subjected to homogenized fusion, so that verification for data of the same modality is not needed any more, and the verification result is more accurate.

The invention relates to the technical field of pollution source supervision, and discloses a pollution source off-site supervision method and system based on big data, and the method comprises the steps: building a dynamic verification rule library through coupling the operation beat data of enterprise key equipment and the total power consumption fingerprint data, and comparing the matching degree between the actual energy consumption and the expected mode in real time and generating a process credibility index. According to the invention, conversion from traditional pollution discharge data verification to production process stability verification is realized, and an unforgeable supervision trust mechanism is constructed through the physical relevance between the equipment start-stop signal and the power utilization characteristic; and meanwhile, the judgment accuracy under the extreme working condition is ensured by utilizing environmental parameter dynamic compensation and micro-differential pressure bypass verification, and finally a quantifiable accumulation enterprise environmental protection credit evaluation system is formed.

The invention provides a commodity traceability management intelligent anti-counterfeiting method and system based on the Internet of Things, and relates to the technical field of anti-counterfeiting traceability of the Internet of Things, and the method comprises the steps: carrying out the vectorization processing of commodity physical feature data, obtaining a unique feature vector, constructing a circulation link structure, and building a bidirectional binding relation; and irreversible Hash transformation is carried out in the circulation event, a node record is embedded, a tamper-proof traceability voucher is formed, and a verification rule set is constructed to carry out consistency and integrity verification. According to the invention, the commodity information can be effectively prevented from being tampered, and the reliability and anti-counterfeiting efficiency of the traceability process are improved.

Systems and methods for validations related to software. In some embodiments, a method for building software with software action validations, the method comprising: accessing a target object type, the target object type comprising one or more object properties; accessing an action type, the action type comprising one or more action parameters, the action type associating with editing a target object of the target object type; generating a set of validation rules associated with the action type, wherein the set of validation rules comprise a local validation rule associated with a rule parameter; and building a software application, wherein the software application comprises the target object type, the action type, and the set of validation rules.

The invention provides a composite QR code verification method and system based on a coding transformation mechanism. The system comprises a code generation system, a QR code generation system and a verification server. During generation, the first code and the second code are generated, the codes are converted, the composite QR code meeting the verification rule can be generated, and the composite QR code can be verified. The composite QR code can be applied to the fields of commodity anti-counterfeiting, process management and the like so as to guarantee the authenticity of the commodity endowed with the composite QR code or the reliability of the process management process.

Systems and methods for automatically updating validation rules used to detect and remediate network operation validation anomalies in conglomerate-application-based ecosystems are disclosed. The disclosed anomaly evaluation platform can dynamically monitor a set of document repositories containing specific guidelines for generating validation reports. In response to detecting updates in the guidelines, the anomaly evaluation platform retrieves a communication map defining parent-child relationships between validation rules and generates an updated communication map. The anomaly evaluation platform detects a transmission of a first network operation to a software application, which uses the first network operation to generate a second network operation. The anomaly evaluation platform provides the first network operation, the second network operation, and the updated communication map to an artificial intelligence model to generate a validation report that meets the specific criteria guidelines.

The invention provides a composite QR code verification method and system. The system comprises a code generation system, a QR code generation system and a verification server. During generation, the composite QR code meeting the verification rule can be generated based on the generated first code and second code, and the composite QR code can be verified. The composite QR code can be applied to the fields of commodity anti-counterfeiting, process management and the like so as to guarantee the authenticity of the commodity endowed with the composite QR code or the reliability of the process management process.

The present invention provides a power grid model verification method based on shape constraints, including the following steps: Step 1, convert the attribute constraints and association constraints in the classes of the power grid CIM into shape constraints on the power grid model RDF data graph; Step 2, convert the basic constraints extracted from the CIM subset and the user-defined power grid model verification rules into a power grid model SHACL shape graph; Step 3, provide the power grid model RDF data graph and the power grid model SHACL shape graph to the SHACL validator for model verification of shape constraints, and output a power grid model verification report.

The invention relates to the technical field of transaction processing process optimization, and provides a task issuing method and device, computer equipment and a readable storage medium, and the method comprises the steps: receiving a template editing instruction through a template library, and generating or modifying a task template based on the template editing instruction; in response to the task release request, calling a target task template from a template library, obtaining task basic information and approval chain information, and configuring task trigger rules including a trigger mode, a complex date rule and a precondition; according to the task triggering rule and the target task template, a task instance containing a form is automatically generated, and a task notification is generated and sent to a preset filling terminal; and when the filling terminal fills in the task form, calling a preset verification rule in the target task template in real time to verify input data corresponding to the task form so as to complete release of a task corresponding to the task form. According to the invention, a universal solution is provided for complex scenes such as financial compliance management and medical data submission.

The configuration method, device and electronic device of the business processing flow provided by the present application relate to the field of data processing technology. In the present application, the data source is configured and processed. The business processing rules of the input data are configured, and the electronic device is used to process the input data according to the business processing rules to output target output data, wherein the electronic device also outputs at least one intermediate processing data in the process of processing the input data according to the business processing rules, and the target output data is obtained by the electronic device processing the at least one intermediate processing data according to the business processing rules. The verification rules of the business processing rules are configured, and the electronic device is used to extract at least one intermediate processing data according to the verification rules to verify the business processing rules. Based on the above method, the problem of poor management and control effect of the business processing flow in the prior art can be improved.

The invention discloses a logistics industry growth member system construction method and system, and relates to the technical field related to online freight platforms, and the method comprises the steps: obtaining core elements for constructing a logistics industry growth member system, abstracting the core elements into dynamically configurable metadata, setting a member grade calculation rule, and sharing a calculation engine; setting a grading bypass verification rule, and verifying the accuracy of a grade calculation result; and according to a verified grade calculation result and a user behavior log, dynamically identifying inactive users for filing, and after core link query is endowed to active users, completing construction of a logistics industry growth member system. Through the design of the invention, the enterprise-level user growth system can realize technical transition from a'chimney type system 'to a'universal platform', and stable support is provided for refined operation.

The invention relates to the technical field of Web application security, and provides a depth context-aware front-end dynamic depth security protection method, which comprises the following steps of: S1, acquiring a current user role, an authority level, an access routing path and semantic attributes of an operation UI (User Interface) component to form multi-dimensional depth context data; s2, the dynamic CSP strategy engine injects the obtained CSP strategy into a front-end environment by creating or updating a page Meta label; s3, performing double-layer protection during operation, wherein the double-layer protection comprises an input protection layer and an operation protection layer; s4, threat linkage response: if a hostile attack is detected in the step S3, a threat event is encrypted and reported to a security policy management center, and the management center dynamically updates a CSP policy and a sensitive operation verification rule; and S5, global strategy optimization: the management center counts and analyzes threat logs, and automatically adjusts a default strategy of high-risk routing. Through dynamic security policy generation, context-aware semantic analysis and a multi-layer protection linkage response mechanism, a self-adaptive and deep front-end security protection system is constructed.

The application discloses a kind of spatiotemporal constraint's blockchain digital collectible dynamic generation method and system, it is related to blockchain technology field, including, digital collectible technical service provider carries out digitization collection and modeling based on multi-view three-dimensional reconstruction technology to physical entity, generates high-precision initial three-dimensional model;The initial three-dimensional model is bound with the environmental data of the physical entity that is collected in real time by sensor network, and the digital twin model of the physical entity is constructed;Intelligent contract is deployed on blockchain, and the preset spatiotemporal constraint condition is defined as the verifiable rule in the intelligent contract;When user client meets the spatiotemporal constraint condition, it submits its spatiotemporal information to the intelligent contract Zero-knowledge proof that the verifiable rule is met.The application evolves initial three-dimensional model, generates final digital collectible file, finally the hash value and metadata of the file are notarized in blockchain, complete casting.

A method, a system, and computer program product for managing container artifacts are provided. An artifact including a container image is received. Validation rules for performing a validation of the artifact are retrieved. Metadata is extracted from the artifact for performing the validation of the artifact. Validation of the artifact is performed by processing the container image using the validation rules and the metadata. The metadata of the artifact is stored, at a database of a registry, for the metadata to be accessible for updates over a lifetime of the artifact.

Systems and methods are provided for generating extract-transform-load (“ETL”) machine learning (“ML”) pipeline validation rules based on user-input, wherein the ETL ML pipeline validation rules may be applicable to validate an ETL ML pipeline against multiple test datasets. The ETL ML pipeline validation rules may comprise compute-type validation rules for computing expected values of data structures within a dataset output by the ETL ML pipeline. The ETL ML pipeline validation rules may comprise check-type validation rules for checking whether data structures within a dataset output by the ETL ML pipeline have intended characteristics.

The present invention discloses a fine-grained access control method and system based on pedigree data. First, the role u of the current user is obtained through the attributes of user au; the result of the user authorization stage is obtained through role u; then the behavior type at is obtained through the action instance; the policy p is obtained through the σ(at) mapping relationship, and the behavior verification rule RuleAV is obtained through policy p; finally, the path rules path rules(ObjectRole, DName) are extracted from the path, and the environmental information atti of the current behavior is extracted using the ha dependency relationship; the object O is obtained through the object role ObjectRole in the path rule, and the dependency path dpath is obtained from the dependency list according to the dependency name using the τ(DName) mapping relationship; starting from the object O, the path rules in the dependency path dpath are used; relevant nodes are found through the θ(O, dpath) mapping relationship and it is evaluated whether the current environmental information meets the requirements during the operation; it is judged whether the behavior can pass the verification rule through the result set, and if it passes, conjunction or disjunction is performed; the present invention realizes finer-grained access control.

Disclosed in the present disclosure are a route configuration method and apparatus, and a device, a medium, and a program product. The route configuration method applied to a subnet comprises: sending a route announcement to at least one network device, wherein the route announcement is used for instructing the network device to generate a corresponding source address validation rule, and the route announcement comprises at least one of the following information: at least two route prefixes and priority indication information corresponding thereto, and at least one sub-route prefix and a parent route prefix thereof.