121 results about "Data life cycle" patented technology

The invention discloses an AI-based automatic connection and handshake protocol for a trusted data space connector. The AI-based automatic connection and handshake protocol comprises a data supply end connector, a data demand end connector and a platform operation end, the data supply end connector is used for collecting and preprocessing data; the demand end connector is used for receiving and processing data; the platform operation end is used for connection management, authority distribution and security auditing; the method has the beneficial effects that through automatic connection and an intelligent handshake protocol, manual intervention is reduced, and the data circulation cost is reduced; multi-factor authentication, dynamic encryption and privacy protection technologies are adopted to ensure the safety of the whole life cycle of the data; aI and machine learning technologies are introduced, so that the system can intelligently select an optimal strategy according to real-time network conditions and data features; interoperation and data sharing among different data spaces are realized, and circulation and value mining of data elements are promoted.

The invention discloses an unmanned aerial vehicle real-time surveying and mapping data fusion method and system based on multi-modal edge calculation, and the method comprises the steps: carrying out the modeling based on the physical characteristics of a sensor, and constructing a multi-source sensor dynamic time synchronization model; dynamically calibrating a space coordinate system of the multi-source sensor through a space registration algorithm under kinematics constraint on the basis of edge computing equipment; based on a multi-modal data fusion algorithm of adaptive weight distribution, obtaining a sensor confidence coefficient and an environment characteristic dynamic adjustment fusion weight; real-time three-dimensional reconstruction is carried out based on an edge computing device, and feature level fusion of point cloud and image data is completed at an unmanned aerial vehicle end; and constructing a distributed edge caching mechanism, and performing data life cycle management based on an LRU algorithm. The method has the advantages that the dynamic synchronization model of the sensor is innovatively constructed, the real-time three-dimensional reconstruction architecture is based on edge calculation, and the space-time consistency of surveying and mapping data in a complex environment is remarkably improved.

The invention discloses a data life cycle management system in a trusted data space, which belongs to the technical field of data management, and comprises the following steps of: counting data from different sources, recording various change operations of the data and generating a data log; performing preprocessing and privacy judgment on the data to obtain the type and sensitive identification of the data; the method comprises the following steps: acquiring various change operations of data, and constructing a data change graph in a directed acyclic graph form; the change operation of the data is monitored by adopting an isolated forest algorithm, and the detection of the abnormal operation is realized; privacy protection is carried out when the data is queried through a preset self-adaptive noise mechanism; performing credibility evaluation on the data according to a preset credibility evaluation index system, and dynamically adjusting the size of the set noise based on the obtained credibility score of the data; according to the method, the acquisition timestamp of the data is obtained and is compared with the current UTC time for judgment, so that a judgment result is obtained, and the data is archived or destroyed.

The invention provides a business hall service system supporting multi-user security data circulation, which relates to the field of electric digital data processing and comprises a multi-user identity and access control module, a security data circulation and isolation module, a data life cycle security management module and a security monitoring and compliance auditing module, the multi-user identity and access control module is responsible for establishing a credible user identity system and realizing fine-grained authority control, and the security data circulation and isolation module ensures encryption protection, integrity verification and effective isolation among multiple users in the transmission process of data; the data life cycle safety management module covers whole-process safety protection of sensitive data from identification, processing to destruction, and the safety monitoring and compliance auditing module ensures that the system continuously meets compliance requirements and timely responds to safety threats through intelligent anomaly detection and whole-link auditing; the system can solve the problems of data security circulation and privacy protection in a business hall service system in a multi-user environment.

The invention discloses an intelligent medical big data information management system, and the system comprises a data collection layer which serves as a sensing neural network, employs an Internet of Things gateway to be compatible with a medical equipment protocol, and deploys an edge calculation node for physiological signal preprocessing; the intelligent preprocessing layer is used for cleaning and standardizing the original data transmitted by the data acquisition layer; the informatization service layer is used for realizing fine-grained authority control based on an RBAC (Role Based Access Control) model, realizing inspection process automation by integrating an LIS (Line Information System) interface through a Hyperdger Fabric block chain evidence storage key operation hash, and constructing a zero-footprint DICOM (Digital Imaging and Communications in Medicine) viewer; the intelligent analysis layer is used for carrying out data life cycle management by adopting a mixed storage architecture, carrying out feature engineering on data, carrying out label matching and classified storage by using efficient neighbor search and similarity / distance measurement, quantifying contribution of each feature or feature combination to a single prediction result through an SHAP value, generating an interpretation result, and outputting the interpretation result; and presenting an interpretation result to a clinician or related personnel through a query interface.

The invention relates to the technical field of data life cycle management, and discloses a dynamic self-adaptive data life cycle management system and method.The dynamic self-adaptive data life cycle management method comprises the steps that a data object and a business lineage log thereof are logically bound, and a lineage entropy value is calculated in a non-semantic counting mode based on the log; according to the method, a data management path which does not depend on an external complex rule engine to carry out event analysis is established, so that a management strategy can be generated by business process records of data in an endogenous and deterministic manner; and meanwhile, for the data which is subjected to high-level control due to accidental high-risk events, after the risk of the data is actually dissipated, automatic falling of the control level is realized, and the coupling degree and the maintenance complexity of the whole management system are reduced.

The invention relates to the technical field of data security, can be applied to business scenes such as financial science and technology, medical health and the like, and discloses a security control method, device, equipment and medium based on hierarchical classification. According to the modal type, selecting a modal recognition agent to recognize the content to obtain a modal recognition result, matching the modal recognition result with a preset knowledge base to generate matching information, and based on the modal recognition result and the matching information, generating a grading classification label of the standardized data object, and executing corresponding security control operation according to the grading and classification labels in a data life cycle link. According to the method, multi-modal data are standardized, hierarchical classification labels are generated by combining modal identification agents with a knowledge base, and driving management and control are carried out, so that the identification integrity and the management and control precision are improved, and the misjudgment and missing detection risks are reduced.

The invention provides a fabricated building full life cycle intelligent management system based on BIM and Internet of Things, and relates to the technical field of intelligent management, and the system comprises a stage data collection module which is used for collecting building data of different life cycle stages; and the life cycle influence module is used for constructing an Internet of Things-BIM collaborative model, generating exclusive digital information in combination with building data, and analyzing the influence of different life cycle stages on building functions to obtain life cycle influence. And the danger coefficient determination module is used for determining danger coefficients of different life cycle stages based on the life cycle influence and the exclusive digital information, and constructing and determining danger thresholds of the different life cycle stages. And the risk traceability module is used for judging whether the danger coefficient exceeds a danger threshold value or not, and if yes, associating the exclusive digital information to generate a risk traceability scheme. According to the invention, the management efficiency can be improved, the cooperation capability is enhanced, the risk assessment accuracy is improved, and sustainable development is promoted.

The invention discloses a sensitive data privacy protection calculation method in a cloud environment, and the method comprises the steps: collecting the flow data of an electric power Internet of Things, and carrying out the structural processing of the collected flow data; under a privacy computing technical framework, performing multi-dimensional privacy feature extraction on the flow data after the structured processing, and identifying sensitive information including a user address, a name and a contact number; wherein a user address in the traffic data is identified by adopting an address self-adaptive identification algorithm; and marking and grading the identified sensitive information, and carrying out monitoring protection according to a grading result. According to the method, a brand-new address tree adaptive identification technology is provided in combination with traffic data characteristics of the power Internet of Things, sensitive data in a cloud computing environment can be rapidly identified, a privacy computing technology is deeply fused, a multi-level protection system is constructed in the full life cycle of the data, and the security and privacy of the sensitive data are ensured.

The embodiment of the invention provides a data life cycle management method and device, electronic equipment and a storage medium, and relates to the technical field of data management.The method is used for improving the flexibility and efficiency of data life cycle management.The method comprises the steps that a management rule input interface is displayed, and a rule configuration area is displayed in the management rule input interface; in response to an input operation triggered in the rule configuration area, management rule configuration information which is input by the input object and aims at the management object is obtained and loaded, the management rule configuration information comprises a strategy rule of each management operation, and the strategy rule comprises a trigger condition and an execution rule of the corresponding management operation; when it is determined that the state monitoring index of the management object meets the triggering condition of the first management operation, the first management operation is executed according to the execution rule of the first management operation, and the first management operation is any one of the management operations.

The invention discloses an automobile part data life cycle safety test system, and relates to the technical field of automobile part data safety. Comprising a data classification and label module, a storage security test module, a transmission security test module, a use and destruction security module, a compliance and risk assessment module, a full-link linkage test engine, a digital twin drive module and an adaptive test process engine. The method has the advantages that data classification, storage, transmission, use and destruction links are dynamically connected in series by a directed acyclic graph through an event-driven workflow orchestrator of a full-link linkage test engine, and fault injection and risk evolution deduction are executed; a three-dimensional twin space link risk propagation path comprising a physical entity model and a data flow topology is constructed by means of a digital twin driving module, full-link detection of cross-link vulnerabilities such as'mismatching of classification labels and encryption strategies' 'permission combination attack ''and the like is realized, and the systematic risk omission ratio is reduced.

The invention discloses an integrated remote teaching assistance and management system for an education scene, belongs to the field of education informatization, and solves the problems that a traditional education system is split in function, tedious in process, high in safety risk and the like. The system integrates three modules: 1) remote call broadcast: supporting home / school / student real-time broadcast notification (including accessory poison check); 2) remote examination and approval: processing and configuring a multi-level examination and approval process, performing state synchronization and preventing tampering of block chain evidence storage; and 3) auxiliary teaching: supporting functions of courseware uploading, homework arrangement, statistics and the like. The data is stored in a relational database (such as MySQL), and the full-life-cycle security of the data is guaranteed through multi-factor authentication, RBAC permission control, high-strength encryption and block chain evidence storage. The beneficial effects are that function integration improves efficiency; security is enhanced through multi-factor authentication and the block chain; an approval specification process can be configured; visual report auxiliary decision making; a high-availability technology (such as WebSocket heartbeat) is guaranteed to be stable, and a whole-process digital and safe teaching management scheme is provided for schools.

The invention relates to the technical field of wireless communication, and particularly discloses a wellhead monitoring data transmission delay processing system based on wireless communication, which comprises a micro-power consumption monitoring terminal, a cloud server, a communication state monitoring module, a priority management module and a delay processing module. According to the scheme, a modular design is adopted, a plurality of units are integrated in the micro monitoring terminal, the internal units are controlled to be powered on periodically through the power supply management unit, the overall power consumption is effectively reduced, a non-contact awakening function is set, the micro monitoring terminal is suitable for sudden task response, the emergency response capability is improved, and remote management, parameter issuing and data synchronization of equipment are realized; the remote interaction capability of the monitoring terminal is effectively improved; according to the method, link sensing and retransmission strategies are combined, delay tolerance and data supplementary transmission capacity are achieved, link abnormity judgment logic is set, uploading tasks are adaptively scheduled according to the link state and the data priority, the transmission reliability is remarkably improved, and meanwhile effective management of the data life cycle is achieved.

The invention provides a compliance governance evidence chain integrity analysis method based on block chain evidence storage, and relates to the technical field of block chains, and the method specifically comprises the steps: S1, collecting related transaction records and evidence storage data in block chain evidence storage records of an evidence chain through a block chain network; s2, managing the life cycle of the evidence chain data; s3, performing hash value comparative analysis on the block chain evidence storage record of the evidence chain to determine the integrity of the evidence chain; s4, carrying out traceability analysis through the evidence chain data; according to the method, the accuracy of data consistency verification can be improved, the normalization and safety of data life cycle management are enhanced, traceability analysis is performed through the causal relationship graph, and the reliability of data traceability evaluation is improved; and through multi-dimensional data analysis and standardized format output, generating an integrity evaluation report.

The present invention relates to the field of data security technology, and discloses an artificial intelligence-based data encryption strategy formulation and data full life cycle security assurance system and method, including multiple public clouds and intelligent encryption and decryption engines, and deploying business systems, databases, encryption judgment service systems and encryption and decryption service systems on multiple public cloud platforms respectively. The intelligent encryption and decryption engine includes a cataloging system, a key management service system and an authorization management service system; by introducing the intelligent encryption engine, cataloging system, encryption judgment service, key management module and artificial intelligence algorithm, the intelligent identification, dynamic update and automatic execution of data encryption strategies are realized, and combined with multiple links such as authorization management and encryption and decryption services, a security assurance system covering the entire data life cycle is constructed.

The invention discloses a data quality dynamic evaluation analysis method and system based on fusion factors. The method comprises the following steps: constructing a multi-dimensional data quality factor set; constructing a dynamic evaluation window based on an aging attenuation function, and automatically adjusting an evaluation cycle of each quality factor according to a data life cycle stage; based on each data quality factor evaluation period, processing a multi-factor conflict problem in the evaluation period through an improved D-S evidence theory; constructing a hierarchical scoring model based on non-conflict factors, and obtaining a comprehensive quality score by adopting an improved entropy weight-TOPSIS fusion algorithm; and constructing an adaptive threshold triggering mechanism, and dynamically adjusting the weight in the data quality scoring model based on the historical scoring standard deviation. The method has the advantages that the data quality evaluation period is dynamically adjusted based on the aging attenuation function, the improved D-S evidence theory is utilized to fuse the multi-factor conflict evidence, and high-timeliness and high-precision dynamic evaluation of the data quality is achieved.

One example method includes receiving, at a node of a data lifecycle management system, a data stream, performing an assessment of the data stream, based on the assessment, assigning a data confidence score to the data stream, providing the data confidence score to an immutable ledger, and performing a data lifecycle operation on the data stream based on a policy to which the data confidence score corresponds. The data lifecycle operation may be performed by the node and may include data processing, data storage, data usage, data archiving, and data destruction.

The invention is suitable for the technical field of traffic management, and provides an urban traffic dynamic command method and system based on digital twinning. According to the method, the high-quality data set is generated through direct multi-source data acquisition, restoration and integration; hierarchical dynamic storage is carried out, and block chain security management is carried out; carrying out stored multi-source data acquisition and processing, and constructing a real-time dynamic traffic twin model; based on the real-time dynamic traffic twinborn model, decision optimization of traffic control is carried out, evaluation feedback is carried out through edge calculation, and model parameters of the real-time dynamic traffic twinborn model are corrected; a three-level data storage system is adopted, a data management center is constructed, and data life cycle management is carried out. According to the method, the real-time dynamic traffic twin model can be constructed by fusing multi-source data, traffic flow simulation, congestion prediction and dynamic optimization are realized, a scientific basis is provided for smart city traffic management, traffic congestion is effectively relieved, and the urban traffic efficiency is improved.

The invention discloses a compliance supervision platform design method based on a full life cycle of spatio-temporal data of an intelligent networked automobile, and belongs to the field of intelligent traffic, Internet of Vehicles and data governance, and the method comprises the steps: according to behavior characteristics of data activities, determining related data life cycle links, and obtaining meta-information of each data life cycle link; based on meta-information of each data life cycle link, a risk perception module is introduced, and the risk perception module comprises a rule engine and a behavior analysis model and is used for recognizing and judging high-risk behaviors in the process in real time; fusing the preliminary risk score and the identification score to obtain a comprehensive risk score; and when the comprehensive risk score exceeds a preset alarm threshold value, automatically triggering an early warning process, and pushing the early warning process to an industry supervision department. According to the method, roles can be configured, review can be traced, and behaviors can be traced back, a landing and extensible technical path is provided for intelligent network connection automobile spatio-temporal data compliance management, and the industry compliance management level is improved.

The application discloses a multi-modal edge computing unmanned aerial vehicle real-time surveying and mapping data fusion method and system, comprising: modeling based on sensor physical characteristics, constructing a multi-source sensor dynamic time synchronization model; based on an edge computing device, through a spatial registration algorithm under kinematic constraints, dynamically calibrating the spatial coordinate system of the multi-source sensor; based on a multi-modal data fusion algorithm of adaptive weight distribution, acquiring sensor confidence and environment feature dynamic adjustment fusion weight; based on the edge computing device, performing real-time three-dimensional reconstruction, completing feature-level fusion of point cloud and image data at the unmanned aerial vehicle end; constructing a distributed edge cache mechanism, and performing data life cycle management based on an LRU algorithm.The application has the advantages that: the sensor dynamic synchronization model is innovatively constructed, the real-time three-dimensional reconstruction architecture based on the edge computing is constructed, and the spatiotemporal consistency of surveying and mapping data in a complex environment is significantly improved.

Apparatuses, systems, articles of manufacture, and methods for data lifecycle management in an edge environment are disclosed. Apparatuses and methods for data lifecycle management in an edge environment are disclosed herein. An example apparatus includes an operation executor to identify a first operation to be performed for a data object at an edge node in an edge environment and a second operation to be performed for the data object, the first operation being different than the second operation. An example apparatus includes a time parameter checker to check a first time value associated with a first operation from a data source and a second time value associated with a second operation from the data source. The operation actuator is for performing a first operation in response to a first time value and for performing a second operation in response to a second time value.

According to the privacy computing data processing method in the data element market provided by the invention, the collected data is encrypted, so that the security of the data in the transmission and storage process is ensured; by adopting a safe storage mode, the safety of the data in the storage process is ensured; according to characteristics and requirements of data, privacy protection algorithms including homomorphic encryption and differential privacy are selected, and calculation and analysis of encrypted data are achieved. Healthy development of the data element market is promoted through data sharing and utilization; when data leakage occurs, measures including stopping using related data and informing a data source party are taken in time so as to reduce loss; in a data processing process, data security risk assessment is carried out regularly, and potential risk points and data leakage risks in risk assessment are identified; and when the data life cycle is ended, the data are safely deleted, so that the data are ensured not to be leaked and abused any more.

The invention relates to an intelligent fusion method for hydrological data from an equipment end to an observation station end, and solves the problem of lack of an intelligent fusion method for hydrological data from equipment data to the observation station end at present and the problem of lack of an end-to-end hydrological data quality evaluation index system capable of being executed in a contrasted manner. According to the method, a method for intelligently fusing multiple sets of equipment data to an observation station end is provided, a quality evaluation index system covering the hydrological data life cycle is innovatively adopted in the fusion process, and when one observation station has multiple sets of equipment, multiple sets of effective equipment data associated with the observation station are integrated into a whole; data quality rating is carried out according to a quality evaluation index system, and equipment data is intelligently fused to a unified observation station end according to a quality rating result and is integrated and stored into a set of observation station data, so that the integrity and reliability of the observation station data can be remarkably improved.

The invention provides a data life cycle autonomous management method and system based on source data feature perception. The method comprises the following steps: defining a basic attribute of target data in the storage system as a triple theta = (t, l, i); establishing a mapping protocol of the source data and the target data; monitoring the change frequency omega of the source data in real time, and executing the following cycle matching algorithm: setting that the life cycle variable and the change frequency of the source data meet an inverse relation t = k / omega, shortening t to improve the sampling precision of the digital clock when omega is increased, and prolonging t to reduce the sampling precision when omega is reduced; and automatically converting the calculated life cycle variable value into a control instruction. According to the method, the data life cycle can be converted into a dynamically programmable variable, low-power-consumption and high-precision response can be realized through hardware acceleration, or a flexible and low-cost management scheme can be realized through software scheduling.

The invention provides a configurable automatic data archiving method and system based on a storage process, and belongs to the technical field of database data life cycle management.The method comprises the following processes that firstly, an archiving task is initialized, and a configuration table archiving rule is loaded; automatically judging and creating an archiving history table; secondly, dynamically calculating an archiving reference date; archiving conditions are generated, and data archiving and source table cleaning are executed in batches; abnormities are processed through log and transaction control, and data archiving and source table cleaning are completed; and finally, task circulation and exception handling are performed, and configurable and automatic historical data management is realized. The method solves the problems that an existing data archiving scheme is high in hard coding dependency, lacks unified configuration, is high in batch processing risk, is weak in fault tolerance and traceability, and is disordered in historical table management, is suitable for batch backup and archiving of historical data and source table cleaning in a core business system, guarantees the performance of a core table, and meets the requirements of data retention compliance.

The application discloses a processing method and device, electronic equipment and storage medium. The method comprises the following steps: obtaining a target storage duration of second data in first data in a target node, wherein the first data is data corresponding to a target service type in target user data of a target user; if the target storage duration is less than or equal to a first preset duration corresponding to the target user, determining to-be-processed data in the first data according to a storage space size occupied by the target user data; and processing the to-be-processed data. The method sets the first preset duration corresponding to the target user, and when the target storage duration of the second data in the first data in the target node is less than or equal to the first preset duration corresponding to the target user, the to-be-processed data is processed according to the storage space size occupied by the target user data, so that the control demand of each user is met on the basis of realizing the first data life cycle management.

The embodiment of the invention provides a data life cycle judgment method and device, a storage medium, computer equipment and a computer program product, and belongs to the field of data life cycle safety management. The method comprises the steps that multiple pre-established life cycle stage rules are established and stored and merged into a rule base, each rule comprises at least one condition item, and each condition item at least comprises a field identifier, a comparison operator and an expected value; analyzing and normalizing the original log of the data security equipment to obtain a standardized log with a unified field structure; matching the standardized logs with life cycle stage rules in a rule base according to a preset sequence; and under the condition that the standardized log is matched with all condition items of one rule for the first time, adding a life cycle stage identifier corresponding to the rule to the standardized log, forming an enriched log, outputting the enriched log, and ending a rule matching process aiming at the standardized log. And the data life cycle division precision and accuracy are effectively improved.

The application discloses an automatic railway network data risk level classification method and device, wherein the method comprises the following steps: determining the ordered attribute and unordered attribute of each data sample in the railway network data based on the data importance level, data life cycle stage, risk type and risk influence degree of each data sample; performing K-means clustering on each data sample based on the ordered attribute and unordered attribute of each data sample, and obtaining a plurality of initial class clusters; performing Gaussian mixture clustering on each data sample based on the cluster center of each initial class cluster and the Gaussian distribution corresponding to each data sample in each initial class cluster, and obtaining a plurality of class clusters corresponding to the railway network data; and determining the data risk level of each class cluster based on the data importance level and risk influence degree of each data sample in each class cluster. The method and device provided by the application improve the effectiveness and accuracy of the risk level classification of the railway network data.

The application discloses a cluster data encryption and decryption method, device and system based on double trusted binding and decryption deadline control, relates to the technical field of information security, and comprises the following steps: collecting hardware characteristic information of a cluster terminal node, extracting a certain length of bytes as original machine code after processing; obtaining a dynamic key factor, extracting a specified length of bytes as a data key after processing; splicing the original machine code and certificate validity period information, generating certificate machine code after processing; splicing the original machine code and certificate validity period information, generating a machine envelope key after processing, performing symmetric encryption on the data key to obtain a machine key; generating a key certificate; and encrypting plaintext data by using the data key to obtain data ciphertext. The application introduces a multi-hardware characteristic fusion and multi-level key encryption system, and solves the problems of device identity impersonation, key leakage and uncontrollable data life cycle in a cluster environment.

The invention relates to the technical field of data life cycle management, and discloses an insurance coupon life cycle data tracking management system, which comprises a data acquisition module, a data processing module, a tracking monitoring module, a risk assessment module, a report generation module and an optimization management module, multi-source coupon data are collected in real time through a life cycle event recording unit and a distributed collection unit in the data collection module, and a data format is standardized by using a data preprocessing unit, so that the problems of information loss and distortion caused by transmission delay and interface abnormality can be discriminated in real time, the accuracy and integrity of coupon state data are ensured, and the data processing efficiency is improved. According to the method, data acquisition errors are reduced, external environment variables and user behavior data are integrated in combination with a multi-dimensional analysis unit, risk model parameters are dynamically updated by utilizing an adaptive learning unit of an optimization management module, the card and coupon risk levels can be dynamically corrected in real time in combination with change factors, and timeliness and accuracy of risk assessment are guaranteed.