3407 results about "Data request" patented technology

The invention discloses a data security sharing method and system, and relates to the technical field of data security, and the method comprises the steps: receiving to-be-shared data uploaded by a data provider; fragmenting the data by adopting a biologically inspired adaptive fragmentation algorithm; generating a digital fingerprint for each fragment by using a multi-dimensional dynamic Hash algorithm; encrypting data fragments by adopting a post-quantum encryption algorithm and storing the data fragments in a decentralized network; recording the access authority, the digital fingerprint and the storage position information to a block chain security account book; when a data request is received, the access permission is verified; carrying out identity verification by adopting multi-mode biological feature recognition; after the verification is passed, obtaining a digital fingerprint and a storage position from the block chain; acquiring the encrypted fragments from the decentralized network and decrypting the encrypted fragments; verifying the integrity by using the digital fingerprint; and recombining the verified fragments to obtain complete data and returning the complete data to the requester. According to the method, efficient data sharing is realized while the data security is guaranteed, and the data value and privacy protection are effectively balanced.

An application server or other processing entity may receive, via a cloud-based platform, user input that may include at least one request for data. The application server may classify the user input into a first of a plurality of deterministic-stochastic spectrum classifications based on the user input and a probability of mapping the at least one request for data to at least one data location. The application server may retrieve the data from the at least one data location and based on the first deterministic-stochastic spectrum classification. The application server may transmit, based on the first deterministic-stochastic spectrum classification and the user input, an input to a large language model. The application server may present a response to the user input, where the response is based on a combination of an output of the large language model and the data retrieved from the at least one data location.

An apparatus for personalization of machine learning models, the apparatus including at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the processor to receive resource data from one or more data acquisition systems, classify the resource data to one or more information categorizations, generate information training data as a function of the classification, train an information machine learning model as a function of the information training data. receive a data request as a function of user input and generate an information output as a function of the data request and the information machine learning model.

The invention discloses a method and a system for realizing mine communication signal improvement based on edge computing, and relates to the technical field of mine communication signal improvement, and the method comprises the following steps: integrating a real-time monitoring system on each edge node, so as to continuously detect the fluctuation of communication flow and data request quantity, the real-time monitoring system identifies a potential communication peak period by collecting real-time data and generates an early warning signal to notify a network administrator or automatically trigger a load management program. According to the invention, through the real-time monitoring and early warning system on the edge node, active monitoring and peak prediction of mine communication are realized, the overload risk caused by traffic surge is reduced, and the stability of data transmission is ensured. And intelligent scheduling and dynamic resource allocation are combined, so that efficient execution of tasks under high load is ensured, and node overload is prevented. A self-adaptive load balancing and feedback mechanism enables the system to dynamically adjust distribution, quickly respond to a bottleneck and improve self-adaptability and stability.

A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) abstracting result data to obtain a data abstraction, the result data being responsive to the one or more data requests, and (v) generating a visualization for the result data based at least in part on the data abstraction.

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.

An apparatus for personalization of machine learning models, the apparatus including at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the processor to receive resource data from one or more data acquisition systems, classify the resource data to one or more information categorizations, generate information training data as a function of the classification, train an information machine learning model as a function of the information training data. receive a data request as a function of user input and generate an information output as a function of the data request and the information machine learning model.

Techniques relate to generating and / or verifying content based on protocols and / or user input. The techniques can receive protocol data from an entity, including a procedure, guideline, policy, or standard. User input requesting content generation related to specific parameters can also be received. Based on the protocol data, a data request can be generated and sent to a content generation component. Machine-generated content can be received from the content generation component in response. The machine-generated content can be analyzed based on the protocol data. Output content can be generated based on the machine-generated content and provided to a computing device. In examples, this ensures that generated content aligns with entity-specific protocols and / or user-specified parameters, enabling tailored and / or compliant content delivery for various contexts.

Systems, methods, and computer-readable storage media for providing a decentralized network. One method includes generating a plurality of tokens comprising cyber resilience data and assigning a plurality of unique identifiers to the plurality of tokens, at least one unique identifier of the plurality of unique identifiers corresponding with at least one token of the plurality of tokens, the at least one token corresponding with one or more access rights for accessing the cyber resilience data. The method includes broadcasting the at least one unique identifier to a data storage, receiving a request for the cyber resilience data of the at least one token, verifying the request based on one or more access controls of the decentralized cyber identity and the one or more access rights, and accessing the cyber resilience data corresponding with the at least one token via the at least one unique identifier.

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.

The invention provides a streaming communication method and device based on long connection and computer equipment, and the method comprises the steps: building SSE long connection between a server and a large model when the server is started; a WebSocket long connection is established between the client side and the server side; the client sends a user dialogue text with the large model input by a user to the server through WebSocket long connection; the server receives a user dialogue text of the client, processes the user dialogue text, generates a corresponding data request, and sends the data request to the large model through SSE long connection; the large model receives the data request, processes the data request, and transmits model output information back to the server through SSE long connection; and the server receives the model output information, processes the model output information, generates a corresponding response message, and sends the response message to the client through the WebSocket long connection. The method has the beneficial effect that the communication efficiency and real-time performance between the client and the large model are improved.

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.

A method comprising: at an importer of an IBOC digital radio broadcasting system: establishing a data link to an audio client configured to buffer audio from an audio source over a buffering duration, to produce buffered audio; receiving, from the audio client, an indication of the buffering duration; identifying a logical channel of an IBOC waveform assigned to the audio client and configured to transmit PDUs of the audio at a PDU rate; computing a quantized number of PDUs that is greater than one into which the buffered audio is to be divided at the audio client based on the buffering duration and the PDU rate; sending, to the audio client, an indication of the quantized number of the PDUs; and upon sending importer data requests to the audio client over the data link, receiving, from the audio client, client data responses each including the quantized number of the PDUs.

The invention provides a trusted block chain data conditional security sharing method and system oriented to a cloud side end, and the method comprises the steps: generating a first re-encryption key for proxy re-encryption for a data request end and a data owning end through a third-party mechanism, generating a DID identifier by the data request end, and transmitting the DID identifier and attribute information to an identity authentication system for registration on a block chain. In a data sharing process, a data owning end performs identity authentication on a data request end based on a decentralized identity authentication system and a challenge response mode, performs authority authentication based on an attribute certificate, and stores data into a decentralized distributed storage system after symmetrically encrypting the data. The access address and the symmetric encryption key are handed to a block chain agent node for uplink storage in a re-encryption form; and the data requester obtains and decrypts the re-encrypted ciphertext, obtains the access address and the symmetric encryption key of the ciphertext of the target data in the decentralized distributed storage system, and obtains and decrypts the target data.

A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) abstracting result data to obtain a data abstraction, the result data being responsive to the one or more data requests, and (v) generating a visualization for the result data based at least in part on the data abstraction.

Provided herein is a process that converts unprotected data into protected data based on permissions defined using logical operators. As such, user permissions can be managed with a simple string of data. In one example, the method may include receiving a request for data from a user device, identifying a permission object corresponding to the user device, retrieving a string comprising a logical expression with a logical operator and one or more values from the permission object, wherein the logical expression defines access permissions of the user device with respect to a database, executing a database query on the database based on the request to generate results, and filtering the results from the database query based on the logical expression to generate filtered results and outputting the filtered results to the user device.

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.

In at least some embodiments, systems and methods of the present disclosure enable content selections for securing communications between agent devices and user devices. A request is received for a communication between an agent device and a user device. A user record associated with the user device is determined based on the characteristic. The security system may obtain content items for authenticating the agent device for the user device with the user record. A set of the plurality of content items are determined for display to the agent device. The set of the plurality of content items are transmitted to the user device associated with the user record. A content item identified by a content item selection is received. A match is determined between the selected content item and the set of content items. The communication is transmitted, responsive to the match, with a predetermined type data request for the user device to satisfy the authentication request.

A data distribution system configured to receive market data from one or more market data sources, associated location data from one or more location data sources, and polygons from one or more polygon sources. The system may normalize the location data and the polygons such that a format of the normalized location data matches a format of the normalized polygons. Upon receiving, via an interactive graphical user interface (GUI), user input comprising a data request, the interactive GUI may determine that the data request comprises at least a portion of the normalized location data. The interactive GUI may augment the normalized location data with one or more normalized polygons, generate an augmented presentation package comprising the one or more normalized polygons, and display the augmented presentation package, such that the one or more normalized polygons are presented on an interactive map interface.

The embodiment of the invention relates to the technical field of semiconductors, and discloses a data management method, system and device for semiconductor process formula parameters and a medium, and the method comprises the steps: carrying out the data analysis of a collected process formula of one or more data formats, converting the data into a target data format, and storing the data in a database; and in response to a data request transmitted through the data interface, returning the corresponding process formula data in the database through the data interface in a data request format based on the configured mapping relationship. Through the scheme of the invention, standardized semiconductor process formula parameter related data can be provided and output to other systems in a standard data structure, and at least the technical problems of low efficiency of checking different equipment parameters, low production management efficiency, frequent errors, high management cost and the like in the prior art are solved.

Various aspects of the present disclosure relate to an authentication server function (AUSF) that receives an authentication request from a security anchor function (SEAF), and transmits a data request for authentication data to unified data management (UDM). The AUSF can receive the authentication data from the UDM for primary authentication, and set an expiration time for security information associated with the primary authentication being successful. The AUSF can then transmit an authentication message of authentication information that includes the security information and the expiration time to an authentication and key management for applications (AKMA) anchor function (AAnF) that registers the expiration time. The AUSF can also initiate reauthentication based at least in part on expiry of the authentication information.

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.

Methods, computer systems, and computer-storage media are provided for generating and using context briefs to identify relevant chat responses. In embodiments, a context template associated with an intent is obtained. The context template includes a data reference referencing dynamic data and content providing context for the dynamic data. Thereafter, a context brief associated with the intent is generated by obtaining the dynamic data and incorporating the dynamic data with the content. Upon obtaining an input data request indicating a user intent, the context brief is identified as corresponding with the user intent of the input data request based on the intent associated with the context brief. A prompt to be input into a large language model is generated. The prompt includes the input data request and the context brief. A response relevant to the input data request is obtained as output from the large language model.

The invention relates to a decentralized information safe and efficient storage and sharing method supporting data verification. The method comprises the following steps: 1) an initialization stage; 2) generating and uploading a ciphertext; 3) evaluating the size of the uploaded ciphertext; if the size of the ciphertext exceeds 256 KB, the IPFS carries out fragmentation processing on the ciphertext, stores the fragments in node servers distributed globally, and generates a unique address identifier at the same time; 4) splicing into a new plaintext; 5) the data provider selects an encryption strategy and performs attribute encryption on the new plaintext; (6) the data requester submits an access application to the Hyperledger Fabric before using the data; 7) verifying the legality of the data request; 8) acquiring a symmetrically encrypted ciphertext; and 9) decrypting to obtain the privacy data of the patient. According to the invention, the paralysis state of the whole system caused by faults of some nodes can be avoided.

The invention relates to the field of wireless communication, in particular to an edge node scheduling system, an edge node scheduling method and an edge node.The edge node scheduling system comprises a data request module, a management back-end module, a performance collector, a scheduler, a predictor and a controller, classifying and putting into a dynamic queue; the management back-end module calls a concurrent reasoning model to process data in batches according to resource and task requirements, and generates a network performance index; the performance collector continuously monitors and collects the indexes and the resource utilization rate; the scheduler formulates a node resource scheduling strategy accordingly; the predictor predicts resource interference and assists the scheduler to make a decision; and the controller switches the model according to the scheduling strategy, adjusts batch size and concurrency number, and realizes dynamic optimization of resources. Through the innovative edge node scheduling framework, localized efficient processing of the data is realized, the execution efficiency of the AI reasoning task is improved, and the resource utilization rate is remarkably improved.

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 relates to an access control method for a data request, and aims to construct a comprehensive security access control system. The method comprises the following steps: receiving a data request of an access client, wherein the data request comprises access identification information and a user identification; and evaluating a risk level based on the request information, and implementing a special control strategy on the high-risk request. The strategy comprises checking a preset access white list and a black list: the request in the white list is directly released, the request in the black list only initiates access authentication to an authorized user, the access is allowed if the authentication is passed, and otherwise, the access is rejected; in addition, access authentication is also carried out on requests which are not listed in a white list or a black list so as to enhance security. According to the method, a multi-level protection mechanism is formed by combining risk assessment, black and white list management and user identity authentication, malicious requests are effectively defended, different users and request characteristics are flexibly adapted, the user experience is guaranteed while the intranet data security is improved, and good expandability and adaptability are achieved.