459 results about "Data content" patented technology

The invention discloses a data transaction security assessment method and system, and relates to the technical field of data security and intelligent assessment. The method comprises the steps of performing feature analysis on a data field, determining a sensitivity weight and generating a sensitivity vector; the fields are graded according to the sensitivity vectors, and dynamic adjustment is carried out in combination with transaction related information to obtain a grading result; calculating a data content risk, a field association risk, and a transaction environment risk based on the sensitivity feature set; determining a weight according to a transaction scene, and weighting various risks to obtain a comprehensive score; and judging the risk level according to the comprehensive score and a threshold value dynamically determined based on historical data. According to the invention, through hierarchical sensitivity modeling and dynamic risk calculation, fine-grained security assessment of different types and sensitivity data is realized, and the risk result can be adaptively adjusted along with changes of data contents, transmission paths and transaction environments, so that the accuracy, real-time performance and scene adaptability of assessment are improved, and the risk assessment efficiency is improved. The defects of a static evaluation method in the prior art are overcome.

The invention discloses a zero-configuration knowledge graph construction method, equipment and a medium, belongs to the technical field of knowledge graphs, and aims to solve the technical problem of how to overcome the hard coding defect in traditional knowledge graph construction, realize a more flexible construction mode with lower difficulty in use, further realize data source entity association and semantic fusion and improve the knowledge graph construction efficiency. According to the technical scheme, field name semantic analysis and data content analysis are conducted through a dynamic semantic analysis algorithm, and intelligent database deep analysis is achieved; the same entities in the multiple tables are automatically recognized and merged through a cross-table entity intelligent merging algorithm, and multi-table collaborative intelligent search is achieved; constructing an intelligent knowledge graph: automatically selecting an optimal construction strategy through a multi-strategy relation construction engine according to keyword role features, and independently constructing a local knowledge graph for each data table; and optimizing and intelligently exporting the knowledge graph.

The invention discloses a smart city data capitalization-oriented data right confirmation management method and system, and belongs to the technical field of data resource management. The method comprises the following steps: receiving data assets uploaded by a user and carrying out multi-modal preprocessing on data contents to generate a data fingerprint with a unique identifier; counting the proportion of the unconfirmed right data fragments; judging an infringement risk level of the data assets in combination with a risk early warning model; if the unconfirmed right proportion exceeds the dynamically calculated threshold value range or the infringement risk level reaches a preset threshold value, executing an audit interception operation and returning a right confirmation abnormity prompt to the user, and requesting to supplement ownership proof; and embedding a multi-modal fusion watermark into the data assets passing the auditing, and generating a cross-domain verifiable right confirmation voucher. According to the method, the data features are extracted through multi-modal preprocessing to generate the unique data fingerprint, the ownership registration state of the data fingerprint is inquired in combination with the block chain technology, the ownership-confirmed and unconfirmed data fragments are accurately identified, and the problem that the data ownership is difficult to accurately and efficiently identify is solved.

Performing charge / showback operations in a large-scale data system by scanning multiple data sources to identify data objects for processing as a unitary group with respect to common characteristics that have an impact on finances within the system. Metadata of the identified data objects are stored in a dynamic dataset that defines a single data access unit for the referenced data objects. The system processes a user query regarding cost allocations, cost forecasts, and resource usage of respective groups within an organization. The query initiates a charge-back or show-back operation that allocates costs associated with each respective usage of resources by a department or cost center, and accesses the referenced data objects through the dataset as a single unit based on data content rather than data location in a file directory of the system.

The invention provides a security optimization encryption method, system and device for data in a facility agriculture scene and a medium, and belongs to the technical field of agricultural informatization security, and the method comprises the steps: carrying out the dynamic division of security levels of data collected in a facility agriculture environment according to the data source device type, data content sensitivity and real-time requirements; distributing an encryption algorithm for the collected data according to a mapping relation between the security level and the encryption algorithm; secret keys are generated and managed based on an identity encryption mechanism, and then secret key fragmentation storage is carried out in combination with a trusted execution environment; when encryption is needed, whether the current trusted execution environment is safe or not is judged, and when the current trusted execution environment is safe, secret keys of the fragments are recombined, the multi-source heterogeneous data are encrypted through the distributed encryption algorithm, and encrypted data are generated; and carrying out secure transmission on an adaptive communication protocol after packaging the encrypted data. According to the method, the data security level is dynamically divided, the encryption algorithm is flexibly selected, the resource consumption is reduced, and the real-time performance and security are improved.

The invention belongs to the technical field of databases, and particularly relates to an LLM-Text2SQL-oriented database table relation exploration method. According to the method, a multi-stage cooperative processing strategy is adopted, database metadata and data content features are integrated, and semantic enhancement and structured completion are performed on original information through a large language model. And on the basis, a potential association candidate set is screened in combination with an algorithm based on feature similarity, multi-dimensional verification and judgment of an association relationship are performed by fusing a predefined rule and a large language model reasoning mechanism, and finally an entity relationship graph supporting interactive editing and iterative optimization is generated. According to the method, end-to-end automatic processing from a heterogeneous database with constraint missing and data integrity impaired to a standardized ER graph is realized, and a solid foundation is laid for remarkably improving the success rate of natural language SQL generation based on a large language model.

The invention discloses a communication method for realizing a BMS protocol through Bluetooth, and the method comprises the following steps: S1, a connection establishment stage: 1) after a local device establishes a Bluetooth connection with a slave device, the local device constructs a request instruction for reading a version number according to a predefined BMS communication protocol; and 2) periodically issuing the request instruction to the slave equipment in a first preset period through the Bluetooth feature with the notification attribute. According to the method, the communication reliability is improved, the problems of instability and data packet loss of a Bluetooth channel are effectively solved through instruction issuing based on timing polling and a multi-level overtime disconnection mechanism, and it is ensured that instructions and data are reachable in a complex wireless environment; and on the basis of a BMS protocol framework, end-to-end CRC16 verification from'equipment address' to'data content 'is introduced in a data analysis link, damaged or tampered data frames in a transmission process can be accurately identified and discarded, and system processing errors or missing data are fundamentally avoided.

The invention relates to the technical field of internet-of-things encryption, in particular to a logistics in-transit data secure transmission system, which comprises a trajectory hash presetting module used for extracting longitude and latitude dotting data according to a logistics transportation plan, arranging the longitude and latitude dotting data according to a time sequence to generate a predetermined trajectory coordinate sequence, and transmitting the predetermined trajectory coordinate sequence to a database; and performing iterative hash operation on the predetermined track coordinate sequence in combination with a time slice index, and storing a check value output by the operation as a reference hash check chain. According to the method, the real-time reliability of each network node can be quantified, so that the evaluation result focuses on the recent behavior performance, finally, the low-trust node is moved out of the routing topology according to the dynamic score, and a safe and purified transmission link is actively constructed; according to the whole set of processing flow, security reinforcement is carried out on a path from a key generation source to data transmission, so that the confidentiality of data content is ensured, and the availability and integrity of data transmission are ensured by dynamically cleaning network infrastructures.

A system for data content feature extraction and evaluation using a hybrid quantum and classical neural network is disclosed. The system receives an input vector that represents digital content and generates a first quantum state vector for the input vector. The system generates a second quantum state vector by performing a quantum convolution operation on the first quantum state vector. The system initiates a second feature vector by mapping each quantum bit within the second quantum state vector to a respective numerical value. The system generates an output feature vector by performing a convolution operation on the second feature vector. The system evaluates the output feature vector by comparing the output feature vector with an expected vector. The system determines that the output feature vector corresponds to the expected vector. In response, the system determines that the output feature vector represents the digital content.

The invention relates to the technical field of ship data management, and particularly provides a ship inspection data intelligent management system and method based on structured storage, and the method comprises the following steps: obtaining a ship number, an inspection item and an inspection number, and constructing a data positioning layer; obtaining an inspection document, performing content analysis on the inspection document, and constructing a data structure layer; obtaining multi-source inspection data, associating the multimedia inspection data in the multi-source inspection data with the data content of the data structure layer, and constructing an association mapping layer; constructing a three-dimensional data storage structure based on the data positioning layer, the data structure layer and the association mapping layer; based on table cell index description, binding the multi-source inspection data to table cells with corresponding semantics, and performing cell data fusion to obtain a plurality of assembly cells; and dynamically reconstructing the inspection document based on all the assembly cells to obtain an interactive inspection document, so that the structural data storage of the inspection data is realized, and the inspection efficiency and the traceability positioning efficiency after data archiving are improved.

The invention discloses an intelligent image batch generation method and device, equipment and a storage medium, and the method comprises the steps: receiving an Excel data file uploaded by a user, carrying out the table structure analysis and data content extraction of the Excel data file, and obtaining target data; obtaining a design template selected by a user, and establishing association between the target data and elements in the design template by adopting a binding algorithm to obtain a binding relation mapping table; an AI image processing function is called to process the bound target data to obtain processed data, and the AI image processing function comprises at least one of AI sectional drawing, AI image sharpening, AI document generation and AI text drawing; based on the binding relation mapping table, applying the processing data to the bound design template to obtain an initial image; and performing image rendering on the initial image through a rendering engine to generate a target image. According to the method, various AI tools are integrated, so that the processing efficiency is remarkably improved.

The invention discloses a distributed document analysis method and device, equipment and a medium. The method comprises the steps that a target to-be-analyzed document is acquired; extracting content feature data of the target to-be-analyzed document; the content feature data is used for reflecting the content complexity of the target to-be-analyzed document; according to the content feature data, determining estimated time consumption for analyzing the target to-be-analyzed document; based on load balancing, according to the estimated time consumption, distributing a target parsing task of the target to-be-parsed document to a target computing power node; and the target computing power node executes the target analysis task to obtain an analysis result. Therefore, the analysis duration is pre-estimated based on the content feature data of the document instead of determining the pre-estimated time consumption singly depending on the size of the document, the method is adaptive to the time consumption fluctuation characteristics of different documents, the precision of the pre-estimated time consumption is improved, calculation power stage distribution is performed based on load balance according to the pre-estimated time consumption, and the calculation efficiency is improved. The resource utilization rate and the load balancing effect of the system are improved.

The invention relates to the technical field of data security, and discloses a data desensitization method and device, a data desensitization gateway and a storage medium. The data desensitization method comprises the following steps: performing sensitive information identification on data passing through the data desensitization gateway, and performing classification and grading marking on the sensitive information; matching a target desensitization strategy corresponding to the sensitive information from a preset strategy library based on the classification and grading mark and the data context information; and based on the target desensitization strategy, executing a desensitization operation on the sensitive information. According to the technical scheme, the sensitive data flowing through the gateway are automatically found, classified and marked through the content recognition technology, and the intelligent dynamic desensitization operation is executed on the sensitive data according to the data content, the context environment and the predefined desensitization strategy, so that the system can automatically adapt to complex scenes, the dependence on manual strategy maintenance is reduced, and the system reliability is improved. The management efficiency is improved, and the optimal balance of the security and availability of the data in the sharing and using processes is realized.

The invention discloses a general data exchange system based on a configurable label structure, which relates to the technical field of data processing and information integration, and comprises a parameter module used for establishing an identity authentication mechanism of two exchange parties; the business document module is used for establishing a data structure definition based on a preset exchange demand; the receipt logic module is used for carrying out logic analysis and code decoupling on the data structure definition, generating a marked language script code and an execution instruction, constructing an execution matrix and realizing mapping between a database physical field and a memory logic variable; and the standard adaptation module is used for comparing and checking the content of the generated data and feeding back a checking result to the parameter module to correct the exchange rule and parameter configuration. A more intelligent logic separation strategy is implemented through structural insight, data reading, writing and transmission are cooperatively controlled, complete decoupling of service logic and program codes is achieved through a nested tag structure, and flexibility, universality and maintenance efficiency of data exchange are optimized.

The invention belongs to the technical field of artificial intelligence, and particularly relates to an AI-based file data content accurate and deep analysis and interpretation method, which comprises the following steps: acquiring multi-format file data and file meta-information, constructing an AI analysis network, extracting text semantic vectors, image visual features, table structure information and document layout features, and constructing a multi-dimensional semantic map. According to a user query intention, semantic extension is performed in combination with a domain knowledge base, an enhanced semantic description vector is generated through a graph attention mechanism, semantic reasoning and relation mining are performed by adopting an improved knowledge distillation Transform model, and a deep analysis conclusion is generated through a multi-hop reasoning model in combination with file data complexity, information density and user requirements. And generating a personalized interpretation report in combination with a user role and a task scene, and outputting an analysis result through a visual interface. Therefore, the problems of poor understanding ability, poor file adaptability and the like in the prior art are solved.

The invention belongs to the technical field of data security, and particularly relates to a community data sharing and exchanging security control method based on a block chain, which realizes fine-grained and dynamic access control by performing refined permission division on user characteristics and data attributes and constructing a verifiable attribute permission mapping relationship in an intelligent contract. The slave logic layer prevents unauthorized access vulnerabilities; a mode of combining a fully homomorphic encryption algorithm and a lightweight homomorphic encryption algorithm is adopted, direct operation of data in an encryption state is realized, a permission verification mechanism without data content leakage is constructed in combination with zero-knowledge proof, and dual protection of'calculation without decryption and verification without leakage 'is formed. According to the method, the data leakage risk caused by smart contract code vulnerabilities is fundamentally immunized, an extensive permission allocation mode is broken through by an attribute-based permission management method, refined permission division can be performed according to actual attributes of users and data, permission abuse and unauthorized access are effectively avoided, and the normalization and security of data access are greatly improved.

The invention provides an automatic adaptation method, system and device for multi-source heterogeneous alarms, a medium and a program product, and the method comprises the steps: receiving alarm requests from different alarm sources through a unified access entry, and extracting path aliases from the path information of the alarm requests, querying corresponding target alarm source configuration information in a preset alarm source mapping relation library; based on the target alarm source configuration information, a corresponding parser is adaptively matched and loaded from a parser resource pool, and the parser supports hot plug loading and unloading; and analyzing the data content of the alarm request by using an analyzer, and converting an analysis result into a unified and standardized data format, so that a downstream processing module executes alarm strategy processing. According to the method, an alarm source identification and resolver dynamic self-adaption mechanism based on path alias is introduced, automatic identification and dynamic adaption of multi-source alarm access are achieved, and the expansibility, reliability and operation and maintenance automation level of the system are remarkably improved.

The invention relates to the technical field of block chains, and discloses a block chain data encryption query method, device, equipment and medium, the method comprises the following steps: extracting data content information of to-be-chained data, using a homomorphic encryption algorithm to encrypt the data content information to obtain ciphertext content information; taking the ciphertext content information and the corresponding ciphertext hash value as on-chain evidence storage data to be stored in a block chain in a chaining manner; performing association mapping on the on-chain evidence storage data and the ciphertext access rule through the smart contract to generate an authority association rule corresponding to the on-chain evidence storage data; performing permission verification on the access permission in the data query request based on a permission association rule; after the permission verification is passed, querying the on-chain evidence storage data in a homomorphic encryption state according to the data query request to obtain an encrypted query result; and decrypting the encrypted query result to obtain target plaintext query data. The reliability of data encryption query can be improved.

The invention provides an associated data acquisition method, a medium and electronic equipment, and the acquisition method comprises the steps: building a business-data circulation dual-domain topology model, and endowing each data node in the business-data circulation dual-domain topology model with a dynamic initial weight; identifying data nodes with strong business semantic association, establishing data association groups, and labeling business semantic tags for data belonging to the same data association group; constructing a cross-service data interaction chain, and generating a basic acquisition baseline according to the data interaction chain; identifying high cross nodes in the data interaction chain; classifying and screening the data nodes; and collecting the data content of each data node. According to the associated data acquisition method, a dynamic data topological associated acquisition mechanism driven by service logic is provided, and accurate acquisition of the service logs is realized by constructing a mapping model of the core service logic and the data flow of the signal system and combining a multi-dimensional weight fusion judgment algorithm and an adaptive content screening engine.

The invention provides a heterogeneous database change synchronization method and device, equipment and a storage medium, and can be applied to the technical field of artificial intelligence. The method comprises the steps of performing structured processing on change data through a pre-trained structured model to obtain data chain information used for representing a data attribution relationship of the change data; performing atlas construction based on the data link information to obtain a change atlas containing data name nodes and data content information; screening out a coincidence area of the database knowledge graph and the change graph corresponding to each heterogeneous database, wherein the coincidence area represents an area with similar data name nodes; and acquiring data corresponding to the content information in the database in the overlapped area as to-be-replaced data, extracting data corresponding to the data content information as target data, and replacing the to-be-replaced data with the target data to complete data synchronization of all the heterogeneous databases.

A client device for managing a distributed document is described. The client device comprises a transfer processor configured to exchange content data with a database, a spreadsheet processor configured to execute a file-based spreadsheet application, and a target processor configured to monitor content locations within a user interface. The transfer processor is configured to receive first content data that includes pre-existing data for a spreadsheet displayed by the application. The target processor is configured to populate first content locations with the first content data according to the identified content locations and capture second content data that is not included in the pre-existing data using content locations identified by a content profile. The content profile identifies content locations for the spreadsheet as displaying static content or user-based content. The transfer processor is configured to store the second content data in the database.

The invention provides a data processing consistency verification method and system based on system internal enhancement verification, and belongs to the technical field of computer system security and data integrity protection, and the method comprises the following steps: setting an enhancement verification enabling identifier for a data instance entering a system internal processing flow; generating an enhanced check value that fuses the data content, the initialized secret value, the runtime perturbation factor, the timing information, and the contextual information; verifying the enhanced verification value in the data processing process; and processing according to a pre-configured strategy when verification fails. The system comprises a management module, a check value generation module, a check value verification module, an exception handling module and a strategy configuration module. On the premise that an existing protocol and an existing system structure are not modified, the tamper-proof capacity of data in the system is improved, the data are prevented from being abnormally modified or replayed or subjected to cross-path error multiplexing, the system safety is enhanced, and meanwhile compatibility and good performance are kept.

The invention relates to the technical field of federated learning, and discloses an image omics-oriented cross-domain federated machine learning training method, which comprises the following steps that: a server distributes a global orthogonal semantic base to establish a shared gradient space recessive semantic coordinate system, and when the stability of a local training process meets a preset condition, a client sends the global orthogonal semantic base to the client; a local gradient is projected to a coordinate system and uploaded together with a digital fingerprint representing the physical characteristics of imaging equipment, and a server groups clients according to the digital fingerprint and performs weighted aggregation based on the information concentration degree on received projection vectors in each group so as to reconstruct a global gradient to update a model. According to the method, through an aggregation mode of firstly performing grouping according to physical causes and then performing weighting in groups according to information values, systematic deviation from equipment differences and real pathological semantics from data contents can be effectively stripped, and sensitivity to key clinical features is kept.

The invention belongs to the technical field of peer-to-peer networks, and particularly relates to a data transmission method and system for collaborative operation of multiple intelligent devices, and the method comprises the steps: collecting sensor feature data, network channel state data and collaborative topological relation data of the multiple intelligent devices; calculating a data content mutation index according to historical statistical characteristics of the sensor characteristic data in the sliding time window; calculating a cooperation space urgency factor according to the position of the local machine, the position of the cooperation equipment and the task state; and generating a dynamic transmission priority according to the data content mutation index, the collaborative space urgency factor and the network load congestion degree in the network channel state data, and performing hierarchical compression transmission on the data according to the dynamic transmission priority, so as to realize data transmission of collaborative operation of multiple pieces of intelligent equipment. According to the invention, the real-time performance and the cooperation efficiency of data transmission of multiple intelligent devices in a complex dynamic environment are improved.

The invention discloses a knowledge base and knowledge graph dynamic access control method and system based on AI classification and grading, and relates to the technical field of data security and access control. Automatically classifying and grading text segments or knowledge graph entities by using an AI model through a data preprocessing module, generating structured tags, and binding the structured tags with original data; after the data are associated and stored to the database through the structured storage module, the authority management module maintains the accessible classification and grade range of the user; and the query filtering module calls the user permission and dynamically filters the retrieval result when the user retrieves, and only returns the authorized content. According to the method, automatic and fine-grained dynamic access control based on data content semantics is realized, the problems of dependence on manual labeling, coarse access control granularity and insufficient flexibility in the prior art are solved, data security and retrieval efficiency are considered, and the method is adaptive to multiple coincidence rules and standards.

The invention relates to the technical field of data compression, in particular to a data compression method and system, which comprises an LZ module, a text stream module, a sequence stream module and an interval entropy coding framework, and is characterized in that the LZ module is used for performing repeated data screening on original data to generate a text stream and a sequence stream; the LZ module screens duplicated data through a hash verification method, specifically, hash values are calculated for input data blocks, the duplicated data are determined based on hash value comparison, and direct data content comparison is avoided; and the character flow module is used for carrying out entropy coding on the character flow. According to the method, an interval entropy coding framework is innovatively proposed, a better probability model is constructed through artificial intelligence and a mathematical method, a better finite state machine is trained, the optimal state machine is used in the compression and decompression process, and the problem that the decompression speed of a neural network method is low is efficiently solved.

This application provides a business data detection method, system, medium, device, and program product, relating to the field of network data security. The method includes: outputting security detection results based on abnormal business data; if the security detection results do not meet a confidence threshold, determining a data object to be invoked based on the abnormal business data; sending the data object to be invoked to a security detection agent, so that the security detection agent can use the data invocation tool corresponding to the data object to obtain security-related data related to the abnormal business data; the security-related data includes at least one of time-related data, content-related data, and identity-related data; and outputting a security detection result that meets the confidence threshold based on the abnormal business data and the security-related data. This application can improve the detection accuracy of business data.

This invention relates to the field of communication management technology, specifically to a remote communication management method and system for inspection equipment based on protocol identification. The method includes the following steps: based on a zoned operation scenario, the structure of the communication data frames of the inspection equipment is analyzed sequentially; field parameters are located and parsed; parameter sets and structure templates are compared; related field combinations are filtered and their overlap is determined; structural differences in consecutive data frames are analyzed; structural misalignment changes are identified; and a sequence offset indicator is obtained. This invention, by combining data frame structure analysis and dynamic feature comparison mechanisms during communication interaction, achieves real-time determination of field arrangement and verification relationships. It adaptively adjusts the parsing and control process according to the data content, possessing the ability to continuously perceive changes in communication structure. This avoids parsing obstacles caused by protocol evolution, reduces manual intervention, and improves the communication consistency, command recognition accuracy, and data interaction continuity of inspection equipment in multi-version mixed access environments.

The invention relates to the technical field of network security intelligence, in particular to an information acquisition scheduling system based on dynamic weight optimization, which comprises a data monitoring and acquisition module, a scheduling queue generation module, a content analysis and feedback module, a crawler execution module and a content analysis and feedback module. Collecting user interaction data, content change rate and the like of a target intelligence source through a data monitoring and collecting module; the dynamic weight calculation module calculates an activeness score, a historical hit rate and a low-frequency protection gain according to the data and fuses the data to obtain a comprehensive final weight; a scheduling queue generation module builds a main queue and a low-frequency guarantee pool according to weight sorting, and distributes differential grabbing parameters; the crawler execution module performs distributed parallel grabbing; the content analysis and feedback module judges validity and feeds back adjustment parameters to form a closed loop; according to the method, the capture coverage rate and timeliness of the low-frequency high-value intelligence source can be improved, the utilization rate of system resources is optimized, and the requirements of network security intelligence for information comprehensiveness, timeliness and accuracy are met.

This invention discloses a data security access control method based on an IoT platform, relating to the field of secure access technology. It includes a dynamic threat assessment step, which determines data risk by analyzing the behavioral sequence of the data parsing process. Specifically, for a specified data type, based on the parsing behavior of historical harmless data samples, a baseline of normal behavior sequence is constructed and its corresponding normal behavior ratio range is determined. Then, the current data to be assessed is parsed, and the real-time behavioral sequence generated during the parsing process is monitored and recorded. This invention overcomes the limitation of traditional access control that only manages who can access the data. By introducing a dynamic threat assessment engine into the access link, it performs in-depth behavioral analysis on the accessed data content itself, constructing a subject-object two-way security system that can effectively defend against data reverse intrusion attacks launched using legitimate data channels.