90 results about "Data life cycle" patented technology

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 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 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.

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 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 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.

The invention relates to a storage method and device, equipment, a storage medium and a computer program product, and the method comprises the steps: receiving a storage request, dividing to-be-stored data according to the life cycle of the data, generating a plurality of data blocks, caching each data block to a corresponding logic disk, and storing the data blocks in the logic disk; and transferring and storing each data block from the corresponding logic disk to the physical disk. Wherein the storage request comprises to-be-stored data. According to the method, the data of the same or similar life cycles in a certain range is divided into one data block, and then the data block is stored, so that the uniformity of the data life cycles can be prevented from being damaged, the disk layout of the storage equipment is optimized, the effect of reducing the garbage collection cost and the write amplification factor of the storage equipment is realized, and the storage efficiency is improved. And the write amplification phenomenon is avoided, so that the storage performance of the storage equipment is improved.

The application discloses a data life cycle management method and system, electronic equipment and storage medium, which are used for improving the reliability of data. The method comprises the following steps: collecting target data through an Internet of Things device, and generating a digital signature bound to the identity of the Internet of Things device; at an edge computing node, verifying and reaching a consensus on the target data and the digital signature based on a dynamic trust evaluation mechanism; recording the data digest of the target data verified by the consensus, an off-chain storage address and verification information used for proving the validity of the consensus into a blockchain; performing compliance verification on the state or operation related to the target data through a smart contract on the blockchain; based on the data entity, the Internet of Things device and the related operation event recorded in the blockchain, a multi-modal heterogeneous graph used for representing the association relationship of the whole life cycle of the target data is constructed; and in response to a query or access request for the target data, a response is provided after taking dynamic privacy protection measures.

The application relates to the technical field of data life cycle management, and discloses a dynamic self-adaptive data life cycle management system and method, which comprises the following steps: logically binding a data object with a business genealogy log of the data object, calculating a genealogy entropy value in a non-semantic counting manner based on the log, and directly determining a life cycle strategy of the data object in a preset strategy mapping relationship according to the entropy value. The application establishes a data management path which does not depend on an external complex rule engine for event analysis, so that the management strategy can be endogenously and deterministically generated from the business history record of the data itself, and meanwhile, the application can also realize the automatic rollback of the control level of the data which is placed in a high-level control due to an accidental high-risk event after the risk of the data has actually dissipated, thereby reducing the coupling degree and maintenance complexity of the whole management system.

The application belongs to the technical field of computer server management, and specifically discloses a user and data full life cycle server management system for a laboratory collaborative environment, which comprises a container virtualization layer, a heterogeneous transaction coordination layer and a data collaboration ecological layer, and a metadata management layer.The container virtualization layer uses Docker containers as user personal computing environment carriers and supports dynamic resource allocation through a "state saving-resource reconfiguration-environment recovery" mechanism.The heterogeneous transaction coordination layer coordinates heterogeneous systems in a Saga transaction mode and realizes cross-system transaction consistency.The data collaboration ecological layer establishes typed management of personal data volumes, shared software environment volumes and public data set volumes, supports software environment encapsulation sharing and version management, and realizes real-time updating and high-performance querying of metadata based on a hot updating architecture of Redis.The application solves the problems of inflexible resource allocation, incomplete environment isolation, permission management dilemma, and difficult data collaboration and recovery.

The invention discloses an intelligent medical data integrated display system based on a block chain, and relates to the technical field of medical block chains, decentralized data management and dynamic access control are realized through a block chain technology, and a patient can define and update an access strategy by using a trusted terminal to ensure data privacy. Attribute-based encryption and zero-knowledge proof technologies are adopted, data encryption storage and anonymous permission verification are achieved, and safe sharing of data is guaranteed. Meanwhile, an emergency access authorization mechanism is introduced, and timeliness and safety in an emergency treatment scene are both considered. In addition, dynamic audit tracking is realized through homomorphic encryption, risks are monitored in real time, emergency response is triggered, and the safety of the data life cycle is ensured. According to the invention, the efficiency, security and privacy protection level of medical data sharing are significantly improved, and the method is suitable for a cross-institution medical cooperation scene.

The invention provides a class imbalance analysis method based on data life cycle evolution. The class imbalance analysis method comprises the following steps: step 1, constructing a full life cycle evolution model of a data sample; 2, performing panoramic scanning and activeness statistical analysis on dynamic indexes of structure response characteristics in different evolution hierarchies; 3, monitoring interaction behaviors among different types of samples in real time in the dynamic propulsion process of the full life cycle evolution model; 4, constructing a number balance mechanism based on life cycle evolution abundance; and 5, training a classification model by using the weighted objective function, and applying the classification model to the test set to realize accurate classification of class imbalance data. According to the method, the optimal fusion coefficient is automatically determined through the Bayesian optimization method with Gaussian process regression as an agent model, blindness of manual parameter adjustment is avoided, and the recognition rate and the overall classification performance of minority class samples are remarkably improved.

The invention discloses a database management method and device and a storage medium, and the method comprises the steps: determining the cycle length of a first index based on a data life cycle feature corresponding to the first index; the number of fragments of the first index in a target period is determined, and the target period is a current period or a future period; and creating the first index corresponding to the target period in the database according to the fragment number and the period length. In this way, the resource storage efficiency of the database can be improved.

A data lifecycle management method, device, equipment, storage medium and program product are disclosed, access heat of all data of a first storage layer in a data warehouse is acquired; wherein the data warehouse comprises at least two storage layers, and there is an association relationship between the storage layers, in which upstream data supports downstream data; cold data in the first storage layer is determined based on the access heat; associated data related to the cold data in the remaining storage layers is determined based on the association relationship; and a data cleaning operation is performed on the cold data and the associated data. By adopting the embodiment of the present application, the problems of hot data misdeletion and cold data redundancy in the data warehouse can be avoided, fine and differentiated management of data is realized, and resource waste of the data warehouse is reduced.

The application discloses a full-life-cycle security management and control system based on data grading. In the data generation, storage, transmission, use, sharing and destruction stages, the data object content features, access subject information, operation behavior records and environment information are collected to construct a unified life-cycle data object set; the data objects are subjected to feature coding and a granular ball clustering method is used to generate a granular ball set; based on the granular ball structure, sample sensitive features are subjected to compression calculation to obtain a granular ball sensitivity representation; the granular ball sensitivity is subjected to grading by using a shadow set model to divide into a high determination zone, a shadow zone and a low determination zone; the granular ball in the shadow zone is subjected to recursive subdivision to obtain a stable grading result; and a mapping relationship between the granular ball and a security policy is established according to the final grading result, and access control, transmission protection, storage protection, use audit, sharing control and destruction disposal policies are executed in different stages of the data life cycle to realize the graded security management and control of the data full life cycle.

The application discloses a short link generation method and device and a medium, and the method comprises the following steps: determining whether the corresponding long-short link mapping relationship exists in the database according to the long link; if the long-short link mapping relationship exists, returning the short link according to the long-short link mapping relationship; if the long-short link mapping relationship does not exist, converting the long link into a short link code according to the short link code generation rule and the table falling rule; determining whether the short link code record exists in the database according to the short link code; if the short link code record does not exist, generating the short link according to the short link code, determining that the short link is successfully generated, storing the long link and the short link code in the database, and returning the short link to the calling party; if the short link code record exists, generating a new long link by adding m random numbers at the tail of the long link; based on the new long link, the steps 2-4 are repeated until the short link is successfully generated. The application solves the problems of poor short link performance, easy data leakage, lack of data life cycle management and the like.

The application provides a compliance governance evidence chain integrity analysis method based on blockchain storage, relates to the technical field of blockchains, and specifically comprises the following steps: S1: collecting relevant transaction records and storage data in the blockchain storage records of the evidence chain through a blockchain network; S2: managing the life cycle of the evidence chain data; S3: performing hash value comparison and analysis on the blockchain storage records of the evidence chain to determine the integrity of the evidence chain; and S4: performing traceability analysis on the evidence chain data; the application can improve the accuracy of data consistency verification, enhance the standardization and security of data life cycle management, improve the reliability of data traceability evaluation through the traceability analysis of a cause-effect diagram, and generate an integrity evaluation report through multidimensional data analysis and standardized format output.

The invention discloses a cluster data encryption and decryption method, device and system based on dual trusted binding and decryption deadline management and control, and relates to the technical field of information security, the method comprises the following steps: collecting hardware feature information of a cluster terminal node, processing the hardware feature information, and extracting a byte with a certain length as an original machine code; obtaining a dynamic key factor, and extracting a byte with a specified length as a data key after a processing result; after the original machine code and the certificate validity period information are spliced, a certificate machine code is generated through processing; after the original machine code and the certificate validity period information are spliced, a machine envelope secret key is generated through processing, and the data secret key is symmetrically encrypted to obtain a machine secret key; generating a key certificate; and encrypting the plaintext data by using the data key to obtain a data ciphertext. According to the invention, by introducing a multi-hardware feature fusion and multi-level key encryption system, the problems of equipment identity counterfeiting, key leakage and uncontrollable data life cycle in a cluster environment are solved.

The invention discloses an encrypted data fragment storage, retrieval and verification method and system based on a decentralized network, and belongs to the technical field of distributed computing and data security. The method comprises the following steps: encrypting to-be-stored data based on attributes and segmenting the to-be-stored data into a plurality of fragments; embedding a unique hidden watermark associated with a fragment identifier and owner information for each fragment; chaining the fragment hash, the watermark information and the storage strategy as metadata; dynamically scheduling fragmented storage nodes through combination of an intelligent contract and node real-time reputation; a hybrid verification mechanism is adopted, the storage integrity is verified in combination with probabilistic spot check and periodic auditing, and the node reputation is updated in real time according to a verification result; and dynamically adjusting the fragment redundancy and the storage position according to the data access popularity, and realizing differential excitation linked with the data life cycle through the smart contract. The system comprises a client module, a decentralized storage node and a block chain network. According to the method, data security, reliable storage, efficient retrieval and adaptive resource optimization are realized, and the method is suitable for a decentralized storage scene.