1960 results about "Data request" patented technology

A computer-implemented method is disclosed. The method includes: receiving a request for retrieval of data satisfying one or more criteria, the request including at least one data request parameter; searching a database storing example queries based on the request to identify at least one matching query; providing, to a large language model (LLM), an input prompt to generate a query purporting to retrieve data satisfying the one or more criteria, the input prompt including the at least one data request parameter and the at least one matching query as an example; and receiving, from the LLM, a result including the generated query.

The invention provides a digital culture product right confirmation and data sharing method and system based on a block chain, and relates to the technical field of digital culture, and the method comprises the steps: generating a comprehensive trust score through a self-adaptive trust evaluation model by fusing timeliness, integrity and consistency trust scores, and constructing a self-evolution data trust network and an encrypted data synchronization channel. After smart contract verification, the access authority of the data requester is determined according to the trust score, access features are extracted through a bidirectional long-short term memory network and a multi-head attention mechanism, a proof chain node is constructed, a mapping relation with an authority confirmation certificate is established by using a graph neural network, and the access contribution degree is calculated through homomorphic encryption and federated learning; and finally, performing income distribution according to a sectional income distribution curve. According to the invention, the problems of difficult right confirmation and low data sharing credibility of digital culture products are effectively solved, and safe and controllable data sharing and income distribution are realized.

The invention discloses a storage node load balancing method and device, equipment and a storage medium, and relates to the technical field of load balancing, and the method comprises the steps: carrying out the real-time monitoring of the state of each storage node, and collecting the real-time load information; predicting the load trend of each storage node based on the real-time load information and the historical load data of each storage node to obtain a corresponding prediction result; and adjusting each storage node and a corresponding data access strategy according to the real-time load information and the prediction result so as to respond to the related data request based on the data copy in the adjusted storage node. Therefore, the storage nodes and the data access strategy can be adjusted in combination with the real-time load information of each storage node and the prediction result of the corresponding load trend; the load change trend of each storage node can be accurately mastered, the storage nodes and access strategies are dynamically optimized, the load balancing capacity of the storage nodes can be improved, and diversified service requirements are met.

A management server system may obtain a request for image data from a computing device. The request may identify a subset of image data to be downloaded and / or streamed to the computing device. The management server system can provide an indication of a storage destination for the image data to a gateway device and initiate upload of the image data from the gateway device to the storage destination. The management server system may monitor the upload and, based on the monitoring, determine the upload is complete. The management server system can cause display of a user interface that includes a visualization of the image data for download of the image data from the storage destination to the computing device.

The invention discloses a TSN scheduling optimization method and device based on flow sensing autonomous learning, equipment and a medium. The method comprises the following steps: deploying a lightweight flow detection module in a switch or a router, and after a controller receives a data request, automatically identifying a newly arrived unknown service flow by using the lightweight flow detection module, and judging whether the newly arrived unknown service flow is a periodic TT flow or an unpredictable burst flow; the controller performs classification management on the identified service flow types, collects topological information and flow requirements of the whole network and issues the topological information and the flow requirements to the terminal nodes through a network management interface; the controller constructs an intelligent queue scheduling task based on the collected network topology information and traffic demand and converts the task into a Markov decision process MDP, network resources, queue states and priorities are used as a state space, a scheduling strategy is used as an action space, a reward function is designed in combination with throughput and delay indexes, and an intelligent queue scheduling task is obtained. Driving a dynamic environment through real-time data and training a DRL model; an enhanced queue scheduling mechanism Pro-CQF is adopted, different priority labels are configured according to classified flow types, and then mixed flow scheduling is carried out; the controller periodically collects time delay, packet loss rate and end-to-end transmission delay indexes and feeds back the indexes to the DRL model, and a scheduling strategy is updated online. According to the method, the traffic sensing and scheduling efficiency is greatly improved in a network environment in which multiple service flows coexist and end-side equipment functions are different, and the reliability and the expandability of the TSN in industrial Internet of Things, edge computing and other high-real-time application scenes are remarkably enhanced.

The invention provides a government affair cloud cross-department data security sharing method and device, and relates to the technical field of data security. The method comprises the following steps: a main chain of a block chain performs first-level verification on a requester based on a VerifyCredate contract and an access policy white list set by a department to which government affair data belongs; the access strategy is a dynamic attribute base access strategy generated by a department to which the government affair data belongs based on a dynamic attribute encryption technology; under the condition that the first-level verification is passed, generating an access credential, synchronizing the access credential to a side chain of the block chain, generating a zero-knowledge proof by the side chain according to the operation log, and initiating a zero-knowledge proof verification request to the main chain to perform second-level verification; and under the condition that the main chain passes the second-level verification, determining a cross-domain trust score between the government affair data requesting department and the department to which the government affair data belongs based on the digital certificate submitted by the requester by adopting a federal model, and performing third-level verification according to the cross-domain trust score. According to the invention, the data sharing security can be improved.

The invention discloses a big language model generation content security test system and method in a black box scene. The system comprises a jailbreak prompt word library module used for storing jailbreak prompt words for performing security test on a big language model; the violation question and answer pair module is used for storing violation question and answer pairs covering different types; the response acquisition module is used for obtaining a data request packet according to query content formed by the jailbreak prompt word and the query request; the security analysis module is used for calculating the similarity between response data corresponding to the query request and an expected violation answer, taking the similarity as a security score, and inputting the security score into the adaptive optimization module; and the adaptive optimization module is used for optimizing the jailbreak prompt words output by the jailbreak prompt word bank module by using a genetic algorithm according to the security score output by the security analysis module. According to the method and the device, the security of the large language model generation content can be effectively tested.

The invention provides a priority resetting method of a cache line and an artificial intelligence chip, and relates to the technical field of artificial intelligence chips, the method comprises the following steps: detecting that a cache group contains a cache line of a first priority state (namely, the priority is greater than a preset level), and in addition, detecting that the cache group contains the cache line of the first priority state (namely, the priority is greater than the preset level); detecting a request state between the processing core and the cache when the target duration (namely the interval duration from the previous access of the data request carrying the priority prompt to the cache group) is greater than the preset duration; when the request state is that the data request sent by the processing core is not detected, spontaneously initiating a priority resetting process, and adjusting the priority of the cache line in the first priority state in the cache group to a preset level; in this way, hardware can automatically reset the priority of the cache line, the situation that the cache line with the high priority occupies the cache space for a long time is avoided, the cache space reserved for non-important data access is improved, the overall performance of the cache is improved, and meanwhile processing of a data request (normal access) of a processing core is not affected.

A method for dynamically rendering a report on the basis of an index model, relating to the technical field of service systems; the technical problems to be solved thereby are how to solve the problem of the inability to dynamically adjust and render a report during development of the report and how to ensure the consistency and accuracy of data. The method comprises the following steps: on the basis of an application scenario, processing acquired service data, and establishing in a backend a summary physical table, a dimensional physical table, and an association between the summary physical table and the dimensional physical table; on the basis of metadata information in the dimensional physical table, constructing a dimensional data model, on the basis of metadata information in the summary physical table, constructing an index data model, and integrating the dimensional data model, the index data model, and a full-dimensional data model constructed in the backend with a front-end interface; and, on the basis of a data request, loading the dimensional data model and the index data model on the front-end interface to form a service report, rendering the service report, and dynamically displaying same. Further disclosed is a system for dynamically rendering a report on the basis of an index model.

The invention discloses a power data management method based on a block chain, and relates to the field of block chains, and the method comprises the steps: initiating a data request; randomly selecting a preset number of oracle machine nodes; segmenting a private key of the request task into a plurality of parts by adopting a threshold key segmentation method; acquiring requested power data from an external data source; verifying the obtained power data; a Byzantine fault-tolerant consensus mechanism is adopted to achieve a consensus for the power data; signing the verified power data through a threshold signature method; the oracle machine management contract performs aggregation verification on the received signature data; the oracle machine management contract returns the power data passing the aggregation verification to the intelligent contract of the data requester; the intelligent contract of the data requester obtains the returned power data through an event monitoring mechanism, and executes corresponding business logic and state updating according to the power data; aiming at the low fault-tolerant capability of an oracle machine in power data management in the prior art, the fault-tolerant capability of the system is improved.

In some implementations, a system may receive the data request. The system may obtain a query associated with retrieving the data responsive to the data request, wherein the query is a first output of a large language model (LLM) that is trained based on metadata associated with a plurality of datasets. The system may retrieve, based on the query, the data responsive to the data request, the data being retrieved from at least one dataset of the plurality of datasets. The system may obtain code associated with providing the visualization of the data responsive to the data request for display, wherein the code is a second output of the LLM. The system may cause, based on the code, the visualization of the data responsive to the data request to be provided for display.

Provided in the embodiments of the present application are a multi-control storage array, a storage system, a data processing method and a storage medium. The storage array comprises a four-control storage module, which comprises two groups of controller pairs and a storage expansion disk cabinet, wherein the two groups of controller pairs are connected on the basis of the Ethernet; either of the two groups of controller pairs comprises two controller nodes, and each controller node is connected to the storage expansion disk cabinet so as to perform shared access to the storage expansion disk cabinet; and a cache unit is provided in each controller node, any controller node determines, after responding to a data write request, a target mirror controller node corresponding to the controller node, and a cache mirror of the controller node is stored in a cache unit of the target mirror controller node.

The invention discloses a cache management system and method, a server, electronic equipment and a storage medium, and relates to the technical field of storage, and the cache management system comprises an acquisition engine used for acquiring a data request stream of an access target; the processing assembly is composed of a load balancer, a plurality of nodes and a processing sub-assembly of each node, the load balancer distributes a data request stream to the plurality of nodes, and the processing sub-assembly is used for providing multi-dimensional features, predicting probability distribution of access targets, determining a pre-fetching target set and determining pre-fetching window parameters at the next moment; and the collaboration component is used for generating a global thermodynamic diagram according to the pre-fetching window parameters of each node at the next moment, finally generating a pre-fetching instruction, pre-fetching the cache from the storage system by using the pre-fetching instruction, and performing multi-dimensional feature fusion through a dynamic window mechanism. The technical problems that a static strategy cannot adapt to a dynamically changing IO mode, resource utilization is low in efficiency and the like in related technologies are solved, and the technical effects of adapting to the dynamic IO mode, improving the resource utilization rate and the like are achieved.

The invention is suitable for the technical field of data circulation, and provides a trusted data space connector layer data circulation method and system, and the method comprises the steps: enabling data to access a trusted data space connector, and carrying out the preprocessing of the data; dynamically configuring an access control strategy according to the identity and authority of the data requester; data are virtualized and circulated among different security domains through a data cross-domain virtualization technology, and in the data circulation process, an end-to-end data encryption transmission technology is adopted; after a data requester obtains the data, the data is processed and analyzed by using a micro-isolation data cross-domain fusion processing technology. According to the method, the fusing index is generated by dynamically fusing the aging feature vector, the frequency risk spectrum and the sensitivity matrix, so that real-time parameter customization and risk adaptive adjustment of the access control strategy are realized, and time sequence change, frequency anomaly and data sensitivity difference in a complex access scene are effectively dealt with; and the dynamic protection capability of cross-domain data circulation is obviously improved.

Disclosed in the embodiments of the present disclosure are a data reading method for a chip, and a chip, a computer device, a storage medium and a computer program product. The method comprises: acquiring a data reading instruction, wherein the data reading instruction is used for instructing data reading to be performed according to reading information and data prefetching to be performed according to prefetching information; on the basis of the data reading instruction, acquiring a first data reading request, wherein the first data reading request includes the reading information and the prefetching information; sending the first data reading request to a cache module, so that in response to the first data reading request, the cache module reads and returns first target data according to the reading information, and pre-fetches and caches second target data according to the prefetching information; and receiving the first target data returned by the cache module. The embodiments of the present disclosure can reduce data request pressure between a request source and a cache module, compress a request bandwidth, improve the performance of a processor, and facilitate flexible control over a prefetching mode on a per-task basis, thereby better satisfying data reading requirements of tasks.

The present disclosure provides an artificial intelligence-based alarm management based on structured time series data and unstructured contextual information where the conventional methods fails to do. Initially, the system receives a user query associated with an industry automation system and classifies into one of a) data request query b) an anomaly detection and diagnosis query c) a log request query and d) feedback for previous response using a query classifier. Simultaneously, the user query is converted into an associated timeseries query representation. Furthermore, a plurality of database queries is generated based on the timeseries query representation using query generator. Further, data pertaining to the user query is retrieved from an associated database based on database queries using Deep Learning models, thereby identifying a critical alarm, and to take appropriate actions if there is any anomaly. Finally, the retrieved data is displayed to the user in a user readable format.

The invention relates to the technical field of electric power communication security, in particular to a power grid data secure transmission system and method based on quantum cryptography and a medium, comprising: a power grid data access module extracts identities of a power grid data request end and a target response end; the quantum key distribution module obtains an original shared key pre-stored by the two communication parties, and generates a quantum key according to the one-time session password and the original shared key; the communication security management module analyzes the shared key information from the quantum key received by the target response end to obtain analyzed shared key information, and performs communication security verification on the original shared key and the analyzed shared key information; and the power grid security communication module encrypts the to-be-transmitted power grid data when the communication security verification result is that the verification is passed, and transmits the power grid encrypted data to the target response end. Through cooperation mechanisms such as quantum key dynamic distribution and security verification, security protection of power grid data transmission is realized, and power grid data communication security is improved.

The invention provides a data security management method and device based on a large model and a storage medium, relates to the field of data security management, and obtains access request information and identity information of a data requester and performs identity verification and auditing. Specifically, firstly, deep fusion and joint verification are carried out through an intelligent verification module so as to understand and process a complex relationship between an identity and a request intention; then, dynamically generating an NFT which has uniqueness and represents specific data access authority, and sending the NFT to a requester; when a requester subsequently initiates an actual data access operation, the authenticity and validity of the NFT are strictly verified, and all access attempts (whether the access attempts are successful or not) and permission changes are recorded on a non-tampering block chain, so that dynamic, fine and highly-credible data access authorization and full-process tracing are realized.

The invention discloses a data security sharing method and system, and relates to the technical field of data sharing. The method comprises the steps that a data provider uploads original data, a privacy budget value is calculated through a differential privacy algorithm, noise is added to obtain noisy data, and the noisy data is processed through an anonymous privacy protection algorithm based on maximum dissimilarity degree clustering to obtain desensitized data; encrypting the desensitized data by adopting a block chain decentralization-based ciphertext policy attribute-based encryption method, obtaining an encrypted data ciphertext, uploading the encrypted data ciphertext to a cloud server, and obtaining a content addressing hash value; encrypting the hash value through an elliptic curve encryption algorithm, and storing the encrypted hash value to a block chain account book; and when an access request of a data requester is received, the cloud server verifies the authority by using a non-interactive zero-knowledge proof protocol and returns an encrypted hash value after passing the verification, and the requester decrypts to obtain the hash value and decrypts the encrypted ciphertext to obtain desensitized data, thereby realizing data sharing.

The embodiment of the invention provides a large language model retrieval enhancement generation-oriented file processing method and device, and the method comprises the steps: carrying out the information extraction and semantic information enhancement of a file according to different file types, and constructing a meta-information structure of the file in combination with an enterprise business scene; dividing the document content into a plurality of structured blocks based on the meta-information structure, and labeling the title and context information of each block; when the file is uploaded, according to the parent directory material quantity and content change of the directory where the file is located, performing dirty marking on the directory; when a data request is received, whether a dirty mark exists in a related directory or not is judged, if yes, the directory is requested to be locked, a summary is extracted from files extracted from bottom to top through a large language model, and the dirty mark is cleared after the summary is cached.

The invention provides a data access control method and system based on zero-knowledge proof, and relates to the technical field of data access control. According to the method, a root key of a unique hardware identity is generated through a physical unclonable function of a data request equipment chip, and meanwhile, real-time running state data of equipment is collected; the two are subjected to cryptographic binding to form an equipment credible state voucher; secondly, detecting capacitance field disturbance when data holding equipment approaches through a capacitive proximity sensor array, and generating an interactive response mode; then, the equipment credible state certificate and the interactive response mode serve as private input to generate a composite zero-knowledge proof, and identity authenticity and physical proximity are proved to data holding equipment at the same time on the premise that sensitive information is not leaked; and after the data holding device passes verification, the data access permission is authorized immediately, and a temporary encryption communication channel is established, so that the reliability and instantaneity of security authentication between IoT devices can be improved.

The invention provides an industrial internet of things method and system based on edge computing, and relates to the technical field of industrial internet of things, and the method comprises the steps: carrying out time-phased dynamic collection and statistical distribution rule analysis on historical welding data requests, including vibration, temperature and current parameter collection frequencies, of edge nodes of a welding robot; and predicting the request quantity distribution of the welding quality analysis service and the equipment state monitoring service in the next period. Real-time response of welding quality analysis is realized through multi-dimensional data prediction and dynamic resource scheduling, a service deployment scheme adaptive to load change is generated under the condition that millisecond delay and energy efficiency constraints are guaranteed in combination with transverse cooperative unloading and a multi-objective optimization algorithm, and the service deployment efficiency is improved. And the edge calculation reliability and the service continuity of the industrial welding scene are improved.

The invention discloses a distributed data consistency management system and method based on a block chain, and relates to the field of block chain distributed data management, the system comprises a client layer, a block chain layer and a storage layer, the client layer comprises a user interface and a data request, the user interface is used for a user and an application to submit a data read-write request, and the block chain layer is used for storing the data request; the data request is used for formatting the request and signing. The data states of all nodes are ensured to be consistent through a block chain consensus mechanism, an intelligent contract automatically executes a consistency rule, human errors are reduced, content addressing ensures that stored data cannot be tampered, a decentralized architecture has no single-point fault, data multi-copy storage improves the fault-tolerant capability, the block chain cannot be tampered, and the data credibility is enhanced. The interstellar file system stores large files, reduces block chain storage pressure, a database efficiently manages metadata and supports complex query, local cache improves hotspot data access speed, and digital signature ensures identity authentication and non-repudiation.

The invention provides a GNSS (Global Navigation Satellite System) network RTK (Real Time Kinematic) differential data broadcasting method and system based on user position sharing, aiming at improving the resource utilization efficiency and the positioning service precision of a network RTK system. According to the method, after a user sends out a differential data request, an existing broadcast product is searched within a certain range, if differential data meeting conditions do not exist, a new broadcast source is dynamically generated according to the initial position of the user, and the error is calculated through a regional ionosphere and troposphere error model and the correlation between the error and the distance and the elevation. Determining a coverage range of the broadcast source; and if the differential data meeting the condition exists, directly sharing the broadcast source. According to the method, resource waste caused by the fact that no user grid point exists in traditional grid broadcasting is avoided, and meanwhile the problem that troposphere correction numbers are inconsistent due to user elevation difference in a single-layer grid mode is solved by dynamically adjusting generation and sharing of broadcasting sources.

The invention discloses an ontology-based data space dynamic access control method and device, and a medium. The method comprises the following steps: constructing a data dictionary connector and a basic connector; establishing a semantic mapping relationship between the global ontology and the local ontology to obtain first access mapping; establishing data field mapping between the data source and the local ontology to obtain second access mapping; performing policy relationship construction on the second access mapping to establish a policy relationship between the data source and the local ontology; obtaining a data request, and determining an accessible field corresponding to the identity of the requester through data access control based on the data request and the first access mapping; carrying out strategy relation analysis on the accessible field to obtain an access query statement; and according to the access query statement, obtaining fine-grained access data through virtual mapping knowledge domain mapping. According to the method, the technical problem that a centralized access control strategy is difficult to respond to the authority change demand in multi-organization cooperation in time is solved.

The invention discloses a data management method based on a real-time data warehouse, and the method comprises the steps: obtaining column type data blocks through vectorization processing according to collected data, dividing data types according to the access frequency of the column type data blocks, and correspondingly setting storage positions; in response to the data request, determining a data access mode according to the cache hit rate of the data request; and according to the real-time monitoring index, a load trend is predicted through a time sequence prediction statistical model, and vectorized nodes and cache capacity are adjusted. Through vectorization processing, cache hit rate analysis and dynamic resource adjustment driven by load prediction, the core problems of low storage efficiency, poor resource utilization rate, high response delay and the like of a traditional data warehouse architecture are solved, and multi-dimensional breakthrough in performance, cost and stability is achieved.

A network system to allow global usage of data while allowing regional jurisdictions control over sensitive data. Different jurisdictions may declare different types of data as sensitive data that is not to be discoverable by another party. The system may receive data that includes encoded data at a first device from a second device (e.g., associated with a remote datacenter). The system may store the data at the first device. In response to receiving a request from a third entity, the system may request a cryptographic key for decoding one or more data fields of the encoded data. Based on decoding the associated field data, the system may transmit a response to the data request that includes the decoded data.

The invention relates to the technical field of data sharing privacy protection, in particular to a cross-industry universal data sharing privacy protection method and a cross-industry universal data sharing privacy protection system. Through data request and identity authentication, generation of a mixed data set, modification of a homomorphic encryption algorithm, data segmentation, ciphertext distribution and secure joint modeling, secure sharing and joint modeling of data between cross-industry enterprises are realized. On the premise that data privacy is guaranteed, cross-industry data value is fully exerted, integration and innovation of industries such as medical treatment and finance are assisted, industry data sharing requirements are met, and industrial collaborative development is promoted.

Methods, and systems for authentication via web components. One of the methods includes: submitting a token request, by a browser application, to a first server entity for a token from an API hosted by a second server entity; receiving, at the browser application, the token and a time to live (TTL) for the token from the first server entity, the first server entity having added an API key to the token request to produce an appended token request and forwarded the appended token request to the API at the second server entity, the API at the second server entity having authenticated the API key and returned the token and the TTL to the first server entity, and the first server entity having returned the token and the TTL to the browser application; and sending, by the browser application to the second server entity, a data request with the token.

A network system to allow global usage of data while allowing regional jurisdictions control over sensitive data. Different jurisdictions may declare different types of data as sensitive data that is not to be discoverable by another party. The system may receive data that includes encoded data at a first device from a second device (e.g., associated with a remote datacenter). The system may store the data at the first device. In response to receiving a request from a third entity, the system may request a cryptographic key for decoding one or more data fields of the encoded data. Based on decoding the associated field data, the system may transmit a response to the data request that includes the decoded data.