2042 results about "Verification system" patented technology

The invention relates to the field of security surveying and mapping, in particular to a network security space surveying and mapping method, system and device based on multi-source data fusion, and the method comprises the steps: obtaining network security data in real time, and constructing a dynamic network topological graph; calculating a time-varying vulnerability score based on the topological graph and a historical attack log, and predicting an attack path and a propagation probability through a Bayesian network; performing cross-domain fusion on equipment, service and user behavior characteristics by adopting a federated learning framework to generate a dynamic asset portrait; generating a risk thermodynamic diagram in combination with spatial autocorrelation analysis and a multi-index fusion algorithm; a defense strategy effect is simulated based on an attack graph reconstruction engine, a Pareto optimal strategy combination is generated through an NSGA-II algorithm, and closed-loop verification and dynamic parameter correction are realized by utilizing honeypot deployment and flow traction. Therefore, the problems of topology update lag, single risk assessment dimension, cross-domain threat association fracture, defense strategy static stiffness, non-closed loop of a verification system and the like in the traditional technology are solved.

The invention discloses an AI agent design platform decision optimization method based on big data, and particularly relates to the field of artificial intelligence, comprising multi-modal data sensing layer construction, a streaming feature calculation engine, a dynamic index fusion center and an adaptive decision matrix. According to the method, accurate synchronous monitoring of the utilization rate of hardware resources and dynamic collaborative optimization of heterogeneous computing units are achieved, and the resource scheduling efficiency in a complex computing scene is remarkably improved; knowledge system degradation caused by long-term learning is effectively prevented, and the continuous reliability of a cognitive system is ensured. The provided multi-dimensional decision credibility verification system is fused with interpretability penetration analysis, environment coupling modeling and logic drift detection technologies, the limitation of a traditional single credibility index is broken through, the risk prediction and fault-tolerant capability of the decision process is remarkably enhanced, and a full-dimensional safety decision guarantee system is constructed for an intelligent agent.

The invention discloses a wide-area landslide rapid identification method based on an interpretable intelligent algorithm, and relates to the field of remote sensing science and technology, and the method comprises the steps: building a dual-channel feature extraction architecture through multi-source spatio-temporal data fusion and knowledge graph dynamic weighting: capturing image local textures through a lightweight CNN, modeling geological spatial correlation through a graph convolutional network, and carrying out the recognition of the landslide. Combining the SHAP value and causal reasoning to generate an interpretable contribution degree thermodynamic diagram and a rule chain; a knowledge graph bidirectional verification system is introduced, spatial logic contradictions are verified by using prior rules, and co-evolution of a model and a rule base is triggered based on misjudgment samples; outputting a multi-dimensional credibility report, quantifying uncertainty by Monte Carlo Dropout, and customizing interpretation granularity according to roles; a terrain-adaptive block-stream processing architecture is adopted, and edge lightweight deployment and federated learning are combined, so that wide-area real-time early warning and model dynamic updating are realized. According to the scheme, the limitation of a traditional black box model is broken through, and a disaster prevention closed loop with physical driving, transparent decision and second-level response is formed.

The invention discloses a multi-modal bill processing method based on dynamic knowledge enhancement. The multi-modal bill processing method comprises the following steps: S1, constructing a dynamic knowledge base containing an aging weight; s2, synchronously processing text, image and format features of the bill by adopting a multi-modal feature fusion network to generate a composite feature vector; s3, semantic-level, format-level and timeliness three-level fusion retrieval is carried out based on the composite feature vector, and a three-level fusion retrieval engine comprises dynamic weighted sorting with timeliness attenuation, a difference degree triggered artificial review mechanism and a policy sensitive slope adjustment algorithm; s4, setting a multi-expert cooperative verification system, wherein the multi-expert cooperative verification system comprises cooperative work of a rule engine, a large language model and a logical reasoning module; s5, implementing a dynamic knowledge updating mechanism, and automatically triggering incremental learning of the knowledge base when policy change or format update is detected; and S6, outputting structured data, and synchronously generating an auditing traceability chain containing a decision path. According to the method, the key field identification accuracy can be improved, and auditing traceability and non-perceptual increment updating in the whole process are realized.

The invention provides a right and interest exchange verification system, belongs to the technical field of right and interest management systems, and effectively deals with complex right and interest fraud through multi-modal dynamic behavior trust chain construction. The system comprises a multi-modal behavior acquisition module, a real-time acquisition input behavior, equipment and environment characteristics, a federated behavior modeling module, a cross-platform construction dynamic behavior baseline library and trust score output module, a scene risk assessment module, a hierarchical verification strategy supporting module, a dynamic scheduling execution module, and an intelligent resource allocation and auditing module. Data desensitization and feature extraction are realized through lightweight edge calculation; federated learning fuses local and global credit scores, and combines a dynamic attenuation model and scene perception weight adjustment; the multi-modal cross validation is used for coping with different risk levels; the intelligent resource scheduling resists the DDoS attack; the system realizes balance between high-precision fraud identification and user experience through behavior continuity protection, confrontation sample detection and interpretable scoring atlas.

A behavioral authorship verification system captures and analyzes multi-modal behavioral patterns during content creation to authenticate human authorship. The system comprises a processor executing behavioral analysis modules that generate comprehensive behavioral fingerprints distinguishing genuine human authors from AI-generated content and impostor authorship. A sentence progression mapping module detects sentence boundaries and captures intermediate composition states including additions, deletions, and modifications. A multi-modal input analysis module monitors keystroke dynamics including flight time and dwell time while detecting paste events and input method transitions. A behavioral pattern recognition engine generates user-specific baselines from historical sessions and computes deviation scores using statistical distance metrics. An anomaly correlation module aggregates behavioral deviation signals using weighted fusion algorithms to detect sophisticated mimicry attempts. An authorship scoring engine synthesizes outputs into unified confidence scores while maintaining temporal authorship chains. The system enables real-time authorship verification during content creation rather than post-hoc analysis.

The invention discloses a food safety sampling inspection data verification method and system and a computer storage medium thereof, particularly relates to the technical field of food safety supervision informatization, and is used for solving the problem of false consistency caused by silent failure when an external data source fails in an existing verification system. Field-level binding is realized by establishing a dependency mapping table of a sampling inspection system and an external data source; constructing a service response causal graph model, and dynamically marking a failure data source based on the deviation between the anti-fact response and the actual response; analyzing the verification field set and positioning a key verification field; degrading the weight of the key field to be below a threshold value and activating a manual auditing flag bit; scanning a preset coupling relationship between fields, freezing associated fields which do not trigger rules, verifying and constructing a conflict topology; when the check engine is executed, dynamically skipping the weight reduction field, suspending the freezing field, and generating a to-be-rechecked report in combination with the artificial flag bit and the topological graph; error data transmission is blocked from the source, and the food safety risk missed judgment rate is remarkably reduced.

The invention relates to an engineering document index consistency proofreading method and system based on a multi-modal large model, and the method comprises the steps: Q1. OCR detection and recognition: carrying out the optical character recognition and format analysis of a source document, converting an uploaded PDF document into a processable text message in a Markdown format, and carrying out the format discrimination of a table, a formula and a plain text; and Q2, table and formula processing: adopting a hierarchical processing strategy, intelligently selecting an optimal processing mode according to the complexity of the table, and converting table information into a descriptive long text through a language large model and cue words. According to the method, accurate, reliable and efficient document index checking service can be provided for a user, the quality and efficiency of professional document processing are remarkably improved, the efficiency and quality of knowledge graph construction are remarkably improved, a knowledge verification system capable of being evolved continuously is established, and the method is suitable for popularization and application. And a reliable technical support is provided for knowledge management and professional decision-making in a complex field.

The invention belongs to the technical field of steel and iron material design, and discloses a stainless steel strength and toughness collaborative optimization method and system based on heterogeneous integration, and the method comprises the steps: constructing a database of stainless steel components, process parameters and mechanical properties; according to the database, establishing a stacked heterogeneous integration model; quantizing contribution weights of input variables of the stacked heterogeneous integrated model to mechanical properties based on an SHAP method, identifying key factors, and setting a multi-target strength and toughness collaborative optimization index to guide an optimization direction; optimal components and processes are screened according to SHAP analysis, a sample is prepared through vacuum melting, hot rolling and heat treatment, the performance is verified according to the ASTM standard, and a final optimization scheme is determined; and a cross-scale digital twinborn verification system is constructed, and collaborative optimization of alloy components, process and macroscopic performance is realized. According to the method, the problems of low efficiency and insufficient generalization ability of a single model of a traditional trial and error method are solved, and an efficient and explainable intelligent optimization scheme is provided for development of high-performance stainless steel.

The invention discloses a network risk assessment model construction method and system based on an AI large model, and relates to the technical field of artificial intelligence and network security, and the method comprises the following steps: S1, a participating node splits a large model into a plurality of semantic independent fragmentation units through a dynamic fragmentation mechanism based on local multi-source heterogeneous data; according to the network risk assessment model construction method and system based on the AI large model, through a dynamic fragmentation federated distillation learning framework, the inherent contradiction between data privacy protection and AI large model training efficiency in cross-mechanism cooperation is effectively solved. A ten-billion-level parameter model is disassembled into semantic independent units by adopting a self-adaptive parameter fragmentation mechanism, the communication overhead is reduced on the premise of ensuring physical isolation of sensitive data in combination with a local differential privacy and parameter confusion technology, and meanwhile, cross-domain fusion of threat features and attack surface blind spot detection are realized through a layered distillation verification system. And the APT attack detection rate is improved.

The invention relates to the technical field of BOM data analysis, and discloses a collaborative BOM data analysis and verification system and method based on an AI model.The collaborative BOM data analysis and verification system based on the AI model comprises an intelligent document sensing and structure analysis module, the intelligent document sensing and structure analysis module monitors and identifies a list file, and sends the list file to a server; and the AI assistant dialogue engine module adopts a language model to interact with an engineer to analyze the document in the unified format field by field. According to the method, a field-level approval mechanism is introduced, each suggestion can be modified after being confirmed by a user, and the user can execute operations such as rejection, remark and pending instead of rechecking only in the final stage, so that the sovereignty, the safety and the traceability of the user are improved, the liability boundary of AI aided design is cleared, the AI is evolved from a tool to an engineering partner with learning ability, and the work efficiency is improved. Interaction intelligent experience is obviously enhanced, and adaptability is high.

The invention discloses an SQL statement structure verification system based on large model and knowledge graph fusion enhancement. The SQL statement structure verification system comprises a knowledge graph construction module, an input design module, a verifier design module and an output design module. According to the method, a knowledge graph is introduced as a structured semantic support, and a closed-loop enhancement processing flow of SQL statements from generation, verification to optimization is realized in combination with a structure perception cue word design, a rule verification mechanism and a Function Call feedback interface; the defects that an existing Text2SQL method is insufficient in structural understanding, lack of semantic reasoning, weak in generalization ability, dependent on computing power and the like are overcome. According to the method, triple guarantee of semantic perception, rule driving and model assistance is realized, the accuracy, robustness and interpretability of SQL generation are remarkably improved, and the cognitive load and operation risk of non-professional users in database interaction are effectively reduced.

The invention relates to the technical field of chip verification, and discloses a chip verification method, test equipment and a chip verification system.The method comprises the steps that a template file is built, a verification environment and a test case are generated based on the template file, a configuration file is obtained, and parameters in the verification environment and the test case are updated through parameters in the configuration file; according to the method, the verification environment and the test case are updated, the updated verification environment and the updated test case are obtained, regression testing is carried out on the chip on the basis of the updated verification environment and the updated test case, the test result is obtained, the verification environment can be rapidly generated on the basis of the template file, parameters can be rapidly replaced, and the chip testing efficiency is improved.

The invention relates to the technical field of block chains, and discloses a block chain and privacy computing collaborative verification system, which comprises a data fragmentation module, a privacy fusion module, a collaborative verification module, a consensus correction module and a fragmentation graph optimization module. The data fragmentation module constructs a multi-stage data collaborative topology through a preprocessing node and a dynamic fragmentation protocol; the privacy fusion module realizes privacy protection by using a ciphertext analysis unit to switch links in a multi-state manner and a zero-knowledge verification unit; a collaborative verification module generates a reference verification strategy through a consensus modeling node multi-dimensional fusion model, and a state optimization unit dynamically aggregates and sorts fragmentation states; the consensus correction module corrects the fragmentation state through an isolation verification unit and a delay compensation unit and calibrates ciphertext parameters; and the fragment atlas optimization module constructs a stability evaluation network monitoring synchronization rate and performs closed-loop adjustment on a verification strategy. The system realizes dynamic fragmentation, privacy fusion and intelligent verification, and improves the efficiency, security and stability of block chain data processing.

Systems and methods for staking instrument cryptocurrency rewards and validator management are disclosed. The systems and methods include generating validator pods associated with cryptocurrency staking validation and generating validator keys configured to be utilized by the validator pods for validating proof of stake operations. A subsets of the validator keys may be assigned to the validator pods and a request to perform the proof of stake operations may be received. A validator pod may be provisioned for validating proof of stake operations, and the validator node may be utilized to validate proof of stake operations based on the selected validator node being a compliant validator node.

The invention discloses a high-availability testing method and system for task scheduling of a computing power host management platform, belongs to the technical field of high-availability testing of computers, and aims to solve the technical problems that in the prior art, high-concurrency scene testing coverage rate is insufficient, cross-domain scheduling, failover and self-healing scene verification are imperfect, and testing efficiency is high. According to the technical scheme, the method structurally comprises the steps of hybrid load testing, wherein the elastic capacity expansion and contraction capacity and the performance stability of a system are verified by simulating a long-time stable load and burst flow scene; cross-regional intelligent scheduling: tasks are dynamically scheduled based on cost, time delay and regional strategies, and optimal resource allocation and service continuity are ensured; resource fault migration recovery: simulating node-level or region-level faults, and verifying the automatic detection, migration and recovery capabilities of the system; monitoring and data collection: collecting affairs, resources and stability indexes in real time, and providing multi-dimensional data support for verification; and analysis and optimization: identifying a bottleneck based on test data to generate optimization suggestions, and continuously improving the high availability of the system.

The invention relates to document verification, in particular to a heterogeneous document set-oriented cross-modal semantic alignment and logic consistency verification system, which is used for heterogeneous document input, supports multi-format document input and comprises multi-modal elements including texts, pictures, tables and charts. The document analysis module is used for carrying out structured extraction on document contents; extracting multi-modal elements, identifying and classifying various elements in the document, and establishing position and type labels of a foundation; the knowledge graph construction module is used for uniformly modeling heterogeneous elements into a multi-modal knowledge graph; the graph neural network semantic alignment module is used for realizing accurate cross-modal semantic alignment by using a specially designed graph neural network based on the multi-modal knowledge graph; the hybrid consistency verification engine is used for performing logic consistency verification in combination with a symbol logic verification mechanism and a semantic consistency verification mechanism; according to the method, the defect that accurate cross-modal semantic alignment and logic consistency verification are difficult to carry out on professional documents with multi-modal elements can be effectively overcome.

The invention discloses a low-vacuum circulating water heating dynamic load matching method based on AI regulation and control, and the method comprises the following steps: step S100, multi-source data real-time collection: building thermal environment parameters are synchronously collected through a temperature sensor array, a vacuum pressure transmitter, a flowmeter and an environment monitoring unit which are deployed in a distributed manner; according to the method, the control period is compressed to the minute level, compared with traditional PID control, the response speed is increased by several times, the indoor temperature can be controlled more accurately, and meanwhile the failure rate of equipment is reduced. According to the sudden weather coping mechanism, heat supply strengthening can be started 30 minutes ahead of time under extreme weather such as snowstorm weather, and the stability of the system is ensured. The method is characterized in that the prediction advantage of deep learning and the optimization capability of model prediction control are deeply combined, and the control problem of multivariable strong coupling of the low vacuum system is solved through a verification system of multi-source data fusion and virtual-real combination.

The invention discloses a distributed data encryption and verification system and method based on a block chain, and relates to the technical field of block chains. The method comprises the following steps: dynamically matching an initial processing node and a transmission path according to data characteristics and node capability; selecting an optimal path and an encryption strategy by combining the node capability, the network state and the data security requirement; data fragmentation encryption transmission is executed, and the transmission quality is evaluated in real time; future transmission risks are predicted based on historical data, and path sustainability is evaluated; and adjusting the path according to the real-time verification value and the prediction feasibility, and updating the block chain record. Full-link traceable auditing is realized through block chain evidence storage, the dynamic encryption strategy and predictive path optimization are combined, the transmission efficiency is improved, the security risk is reduced, the energy consumption is reduced, and the method is suitable for a high-security demand scene.

The invention belongs to the technical field of logistics information, and discloses a multimodal transport trusted data space construction method based on privacy calculation and a block chain. The method comprises the following steps: deploying a modular intelligent data gateway at a core node of a multimodal transport line, unifying the format of multi-source heterogeneous original data, and chaining a hash value; after the multi-source heterogeneous data is subjected to customization processing, key metadata attributes of all the data are registered and linked in real time; constructing a core ontology model, and establishing a cross-domain semantic interoperation capability; establishing a privacy calculation and block chain collaborative dual-channel architecture, and cooperatively training an ETA prediction model in a local data isolation environment by adopting transverse federal learning to ensure that original trajectory data is not out of a domain; constructing a dispute arbitration and credible verification system, and realizing an arbitration process of judicial verification when a transportation dispute occurs; data minimization disclosure and compliance sharing are achieved through dynamic access control. According to the method, multimodal transport data can be available and invisible, and the whole operation process can be audited.

The invention relates to an intelligent energy-saving method for a large building refrigerating system based on a large language model, and belongs to the field of intelligence of large building refrigerating systems. A reinforcement learning framework is constructed, a multi-dimensional state space formed by building thermal loads, equipment operation states and thermal environment parameters is defined, and a dynamic reward mechanism is designed by taking improvement of energy efficiency, guarantee of thermal safety constraints and maintenance of thermal comfort as optimization objectives; developing a word embedding model special for the refrigeration field and a cross-modal decision conversion model, and realizing bidirectional analysis of a natural language instruction and a physical control parameter through feature coding and embedding mapping; and performing low-rank adaptive fine tuning on the pre-trained large language model based on the reinforcement learning experience set, and constructing a closed-loop verification system. Generalized migration and multi-target collaborative decision-making of equipment control strategies are achieved, the self-adaptive regulation and control capacity of a refrigeration system under dynamic loads is improved, and a universal intelligent solution for energy efficiency optimization, thermal safety and comfort is provided for a large building.

A system for authentication includes a validation system and an agent configured to communicate a first credential indicating an identification to the validation system and communicate a second credential indicating the identification to a verification service. The validation system includes a database configured to store authorized user data and a portal configured to provide selection of the verification service from a plurality of verification services. The validation system is configured to compare the first credential to the authorized user data, determine a confidence level of validity of the identification based on the comparison of the first credential to the authorized user data, receive a verification of the second credential from the verification service, and modify the confidence level based on the verification.

The invention relates to a carbon emission checking system and method based on a block chain, and the system comprises a basic resource layer which collects enterprise energy consumption data in real time, employs cloud computing resources to provide data storage and computing capability, and employs a Hash algorithm to process the enterprise energy consumption data, and obtains a data abstract; the block chain network layer carries out distributed storage through an alliance chain architecture, carries out consensus evidence storage on the data abstract by adopting a PBFT consensus algorithm, and generates an encrypted data abstract; the intelligent contract layer receives the encrypted data abstract transmitted by the block chain network layer, and executes verification, calculation and supervision rules; and the application service layer calls the processing result of the intelligent contract layer, and respectively provides an enterprise carbon checking terminal service interface, an institution carbon checking terminal service interface and a competent department carbon supervision terminal service interface for the enterprise, a third-party checking institution and the competent department to check the carbon emission. According to the invention, high-efficiency check, high-credibility verification and whole-process traceable supervision of the carbon emission data are realized.

The invention relates to the field of equipment safety verification, in particular to a wifi router on-line upgrading safety verification method and a wifi router on-line upgrading safety verification system. A wifi router online upgrade security verification system comprises a firmware package construction module, a firmware package verification module and a guarantee activation module. According to the method, a firmware packet header protection logic closed loop is formed through an innovatively designed multi-order composite verification structural body and an anti-offset signature positioning framework; the system can detect the nanoscale tampering of an attacker to the length identification field in real time, cuts off the power supply of the flash memory controller and erases the data buffer area at the hardware fusing level response speed when verification fails, and compared with a traditional scheme, the response efficiency is improved.

The invention relates to the technical field of distributed storage verification, and discloses a storage information verification system based on a consensus mechanism. The system comprises a consensus network communication module, a storage feature analysis module, a verification decision core module, a time sequence prediction module, a decision compensation module and a verification execution engine module. The consensus network communication module is connected with a distributed storage node and receives a storage verification request; the storage feature analysis module extracts multi-dimensional feature vectors of the target data to form a feature descriptor set; the verification decision core module is combined with an embedded consensus verification space and dynamic confidence coefficient constraint condition operation to output an initial verification decision scheme; the time sequence prediction module divides a time window and generates a prediction feature descriptor set; the decision compensation module carries out deviation compensation according to the result to obtain an optimization scheme; and the verification execution engine module sends an instruction to trigger the distributed nodes to execute verification operation. A dynamic verification system constructed by the system adapts to dynamic characteristics and heterogeneous environments of distributed storage.

The invention discloses an off-line function verification system for an intelligent electric actuating mechanism, and the system comprises an off-line function verification unit which achieves the data interaction through the connection with a system signal terminal unit of the intelligent electric actuating mechanism, so as to achieve the off-line function verification function of the intelligent electric actuating mechanism. The offline function verification unit is an integrated module and comprises a man-machine interaction module, a host control module, an interface module, an instruction control module, a control power supply control module and a power supply control module; the problems that a large amount of manpower and time are consumed, the test process is tedious, the work efficiency of the original test process is low, human errors and test record detection errors are prone to occurring, data analysis depends on manpower, and the error risk is increased due to the fact that a traditional test method at the present stage consumes operations such as frequently changing used tools and modifying wiring in the test process are solved.

The invention discloses a real-name DID and biological feature fusion rapid verification system, and the system comprises the following modules: a biological feature processing module which is used for generating a nested biological feature vector; the hash generation module is used for performing hash operation and constructing a Merkle tree; the real-name verification module is used for generating real-name identity data; the DID construction module is used for generating a DID document and adding a BioBinding extension field; the proof generation module is used for generating a verification record; the block chain writing module is used for forming an on-chain real-name DID record; the verification module is used for matching with the on-chain real-name DID record; the confidence control module is used for comparing the matching result with a preset verification threshold value, and if verification is passed, authorized access is completed; and if the verification is not passed, triggering a multi-factor re-verification mechanism to perform secondary verification, calculating a DID confidence value, and if the secondary verification is still not passed, executing identity freezing. According to the method, multi-modal biological recognition and a real-name DID generation mechanism are fused, and on-chain credible verification is realized.

The invention discloses a virtualization hardware verification method and verification system based on a multi-layer architecture, the multi-layer architecture sequentially comprises a first module, an exchange module and a second module, the first module is a client side, and the second module is a simulation side; the verification method comprises the following steps: starting and simulating virtual hardware equipment in a first module by adopting a virtualization platform, and generating hardware behavior data; transmitting the hardware behavior data to the exchange module; the switching module receives the hardware behavior data from the first module and processes the hardware behavior data to obtain target data meeting the requirement of the second module; the processing is to convert the language format of the hardware behavior data generated by the first module into a target language format adaptive to a second module based on a hardware event flow mechanism; the target data is transmitted to the second module, and the second module receives the target data and executes simulation of hardware behaviors based on the target data.

The invention provides a code agent construction system, a construction method thereof and a code generation method, and relates to the technical field of computers, in particular to the technical field of artificial intelligence such as large models. According to the specific implementation scheme, the code agent construction system comprises an intelligent cooperation engine, a layered template library, a semantic understanding and layered retrieval system, a T-RAG generation and optimization system and a closed loop verification system; wherein the layered template library comprises a project-level template, a function-level template and an API-level template; the semantic understanding and hierarchical retrieval system is configured as follows: analyzing user requirements through a natural language understanding module to generate an intention vector, and sequentially executing project-level, function-level and API-level three-level progressive template retrieval; and the T-RAG generation and optimization system is configured to inject the hierarchical retrieval result into the cue word of the large language model to generate deployable codes containing front-end and rear-end logics.

The present disclosure provides for technology that addresses technological challenges arising in the field of identity verification. In particular, the present disclosure provides for out-of-band identity verification workflows that allow a first user to issue a verification challenge to a second user to confirm the identity of the second user. For example, the first user may receive a communication claiming to be from the second user. Rather than attempting to confirm the identity of the second user in-band, the first user initiates an out-of-band verification challenge to the second user.