986 results about "Windows Registry" patented technology

The invention relates to the technical field of financial data processing, in particular to a multi-source heterogeneous fund data processing method and system, and the method comprises the steps: recording source information through building a data source registry, and marking a unique identifier for data; performing differential analysis on the fund data in different formats to generate standardized column type storage data; traversing column type storage data to extract statistical characteristics, performing field classification through metadata analysis and financial dictionary matching, analyzing business connotations of fields difficult to classify in combination with a localized large language model, and mapping the business connotations to a header fusion knowledge graph; generating a mapping rule from the source field to the enterprise-level data model by applying a rule engine template on the basis of field classification and semantic recognition results; converting the data structure according to the mapping rule and executing standardization processing; the quality is further optimized through data cleaning; and finally, the data are verified, standardized fund data supporting data traceability are output, and the strict requirements of financial supervision application are met.

The invention provides a cross-platform dynamic security baseline and vulnerability closed-loop repair method and system based on federated learning, and the method comprises the steps: constructing a heterogeneous policy mapping rule base of a Windows registry, Linux sysctl and iOS plist by configuring a semantic analysis algorithm, and forming a multi-operating system policy consistency guarantee mechanism by combining a configuration conflict detection model of formalized verification; a dynamic reinforcement decision engine is designed based on a vulnerability influence surface analysis model driven by a knowledge graph and a double-circulation reinforcement learning architecture (outer-layer strategy exploration and inner-layer parameter optimization); a special evaluation system is constructed for key fields such as electric power and finance, a domestic cryptographic algorithm is deeply fused, and an electric power monitoring system PCSR / IIR / SCAR multi-dimensional index and SM2 / SM4 / SM9 full-stack security scheme is developed. According to the intelligent security baseline reinforcement method, the problems of wide cross-platform strategy gap, extensive vulnerability repair decision and insufficient industry adaptability of a traditional scheme are solved, and the intelligent security baseline reinforcement method supporting dynamic confrontation, accurate adaptation and service fusion is provided.

Systems for providing multi-access edge computing (MEC) and content delivery. At least one cloud platform and at least one server node are provided. Hypertext Transfer Protocol (HTTP) requests are operable to be send between the at least one cloud platform and at least one edge device. The at least one server node is registered in a cloud platform global registry using an HTTP POST request to a global service address, and the cloud platform global registry is associated with the at least one cloud platform. The at least one server node is operable to create at least one cellular network and provide cellular network services to the at least one edge device. The present invention is also operable to collect and analyze data from an IoT sensor network and take actions based on sensor data using the same node infrastructure and edge computing platform.

Techniques described herein pertain to prioritizing threats based on their potential effect on the specific enterprise network sought to be protected. In one example, this disclosure describes a method that includes collecting, by a computing system and from a plurality of external data sources, threat information; storing, by the computing system and in a threat registry, the threat information that includes information about a plurality of threats; collecting, by the computing system, information about an attack surface for an enterprise network; mapping, by the computing system, the threat information to the attack surface; analyzing, by the computing system and based on the mapping of the threat information to the attack surface, a threat included in the plurality of threats to identify a risk score associated with the threat, wherein the risk score represents an assessment of the vulnerability of the enterprise network to the threat.

The invention discloses a semantic fingerprint adaptive training method for a teaching service robot, and relates to the technical field of education neural network real-time training. Comprising six steps of course version semantic fingerprint injection, real-time drift detection and bucket division positioning, small sample correction and high-level weight patching, hierarchical control incremental learning scheduling, shadow reasoning consistency optimization and learning asset registration and cycle verification and tracking. Measuring drifting in real time by using an information entropy self-adaptive window and multi-scale divergence, generating a lightweight weight patch by small sample contrast learning, and performing online loading; shadow channel parallel reasoning is combined with a grading heat exchange superior weight, four-dimensional learning asset tensor is written into a registry through double-clock witness and chain commitment, random sampling verification and singular value performance verification ensure that assets are consistent with robot online examples, and the comprehensive effects of source traceability, risk self-sensing, model self-repairing and compliance full-chain trace reserving are achieved.

The invention relates to the technical field of protocol services, in particular to an event-driven artificial intelligence context protocol service registration and discovery method. The method comprises the following steps: firstly, receiving a service instance registration request, constructing a service registry, and recording a service address and capability description; obtaining the health state of the instance through heartbeat detection; monitoring the state change and converting the state change into a standard event; the SSE technology is adopted to establish long connection and push the filtered events in real time; client connection is maintained, and automatic reconnection and session recovery during abnormity are realized; service capability is analyzed based on semantic comprehension, and accurate matching of requirements is realized; millisecond-level state perception is realized, polling overhead is avoided, service continuity is ensured through intelligent matching and session recovery, and the method is suitable for high-real-time intelligent agent application scenarios.

The invention discloses an event early warning efficient management method and system based on park management, and relates to the technical field of safety management, and the method comprises the steps: constructing a hexagonal cellular unit layout, generating an equipment registry and a network topology structure, and forming a structured data set through data alignment and sliding window verification; the edge server loads an initial weight, calculates a dynamic weight matrix based on the LSTM network, and generates a high-order feature vector set in combination with the graph neural network; inputting the high-order feature vector set into a space-time prediction model to generate an environment evolution trend prediction value, fusing network topology and BIM model parameters to calculate a dynamic risk index, and triggering graded early warning; the command center analyzes the early warning signal to generate a fusion visual interface, historical cases are matched through federal learning, a resource allocation scheme is optimized, and an optimal disposal strategy is output through Monte Carlo simulation. By dynamically adjusting the weight of the sensor, the weight of the infrared sensor in the high-temperature-sensitive area is increased, and the abnormality capturing efficiency is improved.

A decentralized artificial intelligence platform is disclosed that enables secure sharing and execution of AI modules in sensitive application domains. The platform comprises a knowledge module registry for discovering specialized AI modules, a security framework enforcing structural integrity of AI modules, a zero-knowledge proof validation service for verifying usage conditions without exposing private data, and a blockchain-based value chain for managing smart contracts and payments. In operation, an AI agent can fetch a required AI module from the knowledge module registry, prove the right to use it, execute the AI module on local data, and automatically pay the AI module's provider through a blockchain transaction.

In one embodiment, a method includes detecting a change in context of a computing system to a current context, changing a first registration status of a first set of actions with an assistant system associated with the computing system based on the change in context to the current context, where the first application is in a foreground of a user interface of the computing system, changing a second registration status of a second set of actions with the assistant system based on the change in context to the current context, where the second application is in a background of the user interface of the computing system, updating a list of registered actions for the assistant system based on the changed first and second registration statuses, and storing the updated list of registered actions on the computing system.

An illustrative data platform is disclosed that may monitor a compute asset within a compute environment. This monitoring may include receiving registry data collected, by an agent deployed to the compute asset, from a registry space of the compute asset. Based on the registry data collected by the agent, the data platform may determine that a change within the registry space of the compute asset is associated with a security threat to the compute asset. Accordingly, based on the determining that the change within the registry space is associated with the security threat, the data platform may perform an action configured to facilitate remediation of the security threat. Corresponding methods, systems, and products are also disclosed.

A computerized platform enables secure, policy-compliant creation, governance, and monetization of digital artifacts produced by Al-driven “persona” agents in regulated domains (e.g., healthcare, finance). For each agent session, a federated compliance-token generator issues a cryptographically signed token embedding the full delegation chain, credential lineage, real-time policy snapshot, monetization rules, expiration and revocation data. As artifacts or workflows cross organizational or jurisdictional boundaries, a token inheritance module can subdivide, transfer, renew, or revoke the token while appending each event to an immutable, cryptographically linked audit trail. Every agent output is encapsulated as a digitally signed artifact that is indelibly linked to its originating compliance token and enriched with provenance, consent, and service metadata. A permissioned blockchain (or sharded distributed ledger) functions as an asset registry that immutably stores artifacts, tokens, and chronological records of creation, access, transfer, consent change, and policy updates. A smart-contract engine automates revenue allocation and settlement, ensuring continuous traceability, privacy protection, and financial compliance across institutional boundaries.

The invention discloses an MCP-based multi-agent collaboration method and device and a medium, and relates to the technical field of artificial intelligence, the method comprises the following steps: obtaining a model registry form through a standardized model registration interface, analyzing model metadata in the registry form, and extracting a core field of a current registration model; creating a model node in the model map, and initializing the model node based on the core field; receiving a task request, triggering a scheduling engine, determining a plurality of candidate model nodes in the model atlas according to task content, respectively calculating task execution scores of the candidate model nodes, and generating a model execution chain based on the task execution scores; and based on the model execution chain, scheduling a candidate model corresponding to the candidate model node, and executing the corresponding task content. Dynamic access of multiple types of models is supported through a standardized model registration interface, system expansibility and integration efficiency are improved, and matching precision of tasks and models and multi-model cooperation continuity are enhanced.

A system including at least one processor and non-transitory computer-readable storage storing instructions that, when executed by the at least one processor, cause the system to: generate a context configuration module programmed to compose a user experience based on a user context and a registry of micro front-ends; and generate a rendering module programmed to render one or more micro front-ends from the registry of micro front-ends into a framework to deliver the user experience.

Methods, systems, and devices for data management are described. A data management system (DMS) may obtain metadata associated with a snapshot stored by the DMS and including information associated with data paths in the snapshot. The DMS may scan an index registry for identifiers of the data paths to determine whether the index registry includes namespace and hierarchical index information that map the data paths to path identifiers and to descendent data paths within the snapshot, respectively. The DMS may generate term and count index information based on the metadata. The term and count index information may map terms to data paths that include the terms and numerical values associated with the terms, respectively. The DMS may store, in the index registry, the term and count index information with an identifier of a corresponding index group. The namespace and hierarchical index information may be common to multiple index groups.

An end-to-end rendering system enforces policy-constrained, symbolic presentation of artificial-intelligence (AI) outputs prior to any pixel emission. An AI accelerator emits inference tokens as (token identifier, confidence, domain tag) tuples into an output FIFO. A graphics processor with a command processor and SIMD co-processor executes a policy engine that runs a deterministic finite automaton (DFA) stored in non-transitory memory. The DFA consumes the tuples and produces, before any frame-buffer writes, a permit / deny decision and a visibility mask that constrain presentation attributes. A glyph selector maps permitted tuples to entries in a constrained glyph dictionary specifying a glyph identifier, semantic class, and allowed substitutions. A provenance tagger computes a cryptographic hash over at least the glyph identifier, a DFA-state policy identifier, a session nonce, and a checksum of the tuples to create an evidence capsule bound to the glyph. A device-aware renderer, consulting a device profile registry and a rendering grammar, emits a renderable asset for the glyph only when permitted by the visibility mask and grammar. A justification ledger records, for each displayed glyph, the evidence capsule and a monotonic timestamp. Executed entirely within the graphics processor, the pipeline prevents unauthorized tokens from entering the display path, enables cryptographically verifiable traceability of visible content, and reduces bandwidth by representing outputs as glyph identifiers rather than text or raster imagery, while allowing runtime policy updates without modifying the underlying inference model.

Various aspects of the subject technology relate to systems, methods, and machine-readable media for cross-chain communication in a blockchain platform. Various aspects may include accepting, at a first blockchain, a first transaction including a message and a message payload. Aspects may also include validating, at the first blockchain, the message by signing the message using signature keys of one or more validators in a first set of validators of the first blockchain. Aspects may also include generating an aggregate signature based on the signature keys of the one or more validators in a first set of validators. Aspects may also include submitting a second transaction on to a second blockchain, the second transaction including the message and the aggregate signature. Aspects may include validating, at the second blockchain, the second transaction based on a shared registry.

The invention discloses a cross-domain identity authentication and access authorization method, system and device and a medium, and belongs to the field of Internet of Things. According to the method, a unified identity authentication mechanism and a dynamic authority control model are constructed based on a decentralized identifier and a block chain technology. Firstly, an Internet of Things entity submits decentralized identifier information through an identity authentication request; the system generates identity metadata according to the request and records the identity metadata to an identity registry, and meanwhile, constructs a decentration identification document and stores the decentration identification document to a verifiable data registry. And then, the authorizer executes point-to-point trust evaluation based on the identity data and the on-chain traceability information, and generates a verifiable certificate with an encrypted signature. And the verifier completes certificate verification through an intra-domain or cross-domain verification mode, and dynamically grants the authority according to the trust value and the access policy directory. Cross-domain trust migration and dynamic permission adjustment are supported, and the identity authentication security and the access control flexibility in the multi-domain environment of the Internet of Things are improved.

Methods, systems and apparatuses for sharing video data across tenants of a multi-tenant security system. The methods may include maintaining a first tenant account of a security server and a second tenant account of the security server. The first tenant account is unrelated to the second tenant account. The second tenant account is configured to include partner account privileges for the first tenant account. A request from the second tenant account to access a resource associated with video data included in a resource registry of the first tenant account is accessed. The resource registry is made accessible to the second tenant account based on the partner account privileges. The request may be approved or denied. The video data is stored in a tenant database in association with the second tenant account based on the request being approved. The request may be processed by an image processing device.

An apparatus for an Internet of Things device registry display includes a user input processing circuit structured to interpret one or more user input command values, an Internet of Things Universal Identification (IoT UID) identification circuit structured to determine one or more IoT UIDs, based at least in part on the one or more user input command values, a device lookup circuit structured to: generate a query that includes the one or more IoT UIDs, and retrieve device property data corresponding to the one or more IoT UIDs, a query provisioning circuit structured to transmit the query to an IoT device registrar server, a device property processing circuit structured to interpret the device property data generated by the IoT device registrar server in response to the query, and a display circuit structured to display the device property data with the corresponding one or more IoT UIDs.

The present invention relates to method for changing the value of one or more privacy parameters, such as a MAC address, of target stations within a BSS, at both an AP station and a non-AP station associated with the AP station. The two stations share a pseudo-random function to generate the new values of the privacy parameters from a shared key and a shared parameter whose value varies over time. The methods comprise for each station: obtaining the shared key and parameter value; communicating, with the other station, a request for changing the values of the privacy parameters at a target time; calculating the new values by using the shared key and the current value of the shared parameter as inputs of the shared function; and replacing, in a registry, the current values of the privacy parameters of the target station by the calculated new values at the target time.

The invention discloses an architecture method based on a video edge AI inference cluster, and relates to video data processing, the method comprises the following steps: configuring an inference cluster comprising a plurality of edge devices and accessing a server; the server specifies the identity of the edge device and configures a load registry, the main device obtains the load registry through the server and establishes a distribution decision, and the main device obtains a video stream of the data acquisition node and decodes and converts the video stream into a picture format to obtain a plurality of continuous first image data; meanwhile, the master device accesses a load registry and sends the first image data to a corresponding slave device according to a distribution decision, and the slave device calls an inference model to perform an inference service; the method aims to improve the situation that when a current edge device carries out AI reasoning, due to resource limitation of the edge device, resource distribution is uneven or waste is caused.

A content tracking system may include a processor. A content tracking system may include a non-transitory memory coupled to the processor, including one or more content containers. A content tracking system may include a communication service coupled to a network interface, the communication service configured to receive content-related service requests. A content tracking system may include a content container service communicatively coupled to the processor. A content tracking system may include a registry container service communicatively coupled to the processor, wherein the processor is configured to. generate a content container package, associate a data content portion with the content container package, generate side car file data, associate the side car file data with the content container package; and log a plurality of content-related metadata attribute values to a registry database.

A computer implemented method can receive an incoming query statement and search a query hint registry for a patterned query statement that matches the incoming query statement. A wildcard expression contained in the patterned query statement matches one or more characters of the incoming query statement. The query hint registry includes a statement hint paired with the patterned query statement. Responsive to finding the patterned query statement that matches the incoming query statement, the method can append the statement hint to the incoming query statement, obtain a query execution plan for the incoming query statement appended with the statement hint, and execute the query execution plan.

Mechanisms are provided for identifying vulnerability chains in a computing system. Computer system vulnerability characteristics for a plurality of computer system vulnerabilities from a vulnerability registry are retrieved. For each vulnerability, a threat score is calculated indicating a level of risk of the vulnerability to security of the computing system. Based on the vulnerability characteristics and the threat score, a directed acyclic graph (DAG) data structure is generated having a plurality of vulnerability chains, each vulnerability chain having a plurality of vulnerabilities, represented as nodes of the DAG, linked to each other from a root node to a terminating node. Links of the DAG have weights corresponding to a function of the threat scores of the nodes directly connected by the link. A graphical representation of the DAG is generated that depicts the weights of the links to thereby represent relative threat of the vulnerabilities linked by the links.

The technology disclosed herein enables identifying, in a container registry, a plurality of containers corresponding to a plurality of continuous integration (CI) components for continuous integration, deploying, to an execution environment, the plurality of containers, identifying, based on a configuration script, a dependency between a first container of the plurality of containers and a second container of the plurality of containers, and configuring, based on the dependency, the second container to access data of the first container. Each container of the plurality of containers corresponds to a CI component of the plurality of CI components.

A method for determining a trust indicator is provided. The method may include interpreting, via an Internet of Things Universal Identifier (IoT UID) processing circuit, an IoT UID corresponding to a device and identifying, via a record management circuit and based at least in part on the IoT UID, a record in a database corresponding to the device. The method may further include determining, via a trust analysis circuit and based at least in part on the record, a risk indicator of the device and transmitting, via an indicator provisioning circuit, the risk indicator.

A computing device receives a container image from a container registry, the container image comprising a plurality of layers. The computing device extracts, from the container image, a plurality of files into a filesystem of the computing device, each file of the plurality of files corresponding to one of the layers of the plurality of layers. The computing device generates a metadata file that describes a directory structure of the plurality of files in the filesystem. The computing device mounts the metadata file to a location in the filesystem, wherein mounting the metadata file causes a digest of the metadata file to be generated and the metadata file and the plurality of files in the filesystem to be read-only.

The invention discloses a data exchange method and device for a trusted data space and a medium. The method comprises the following steps: establishing a verifiable registry and a distributed digital steward of a trusted data space; registering a data space main body ID for each main body of the trusted data space, and signing and issuing an identity certificate for each main body based on the data space main body ID; according to the identity credentials and the private keys of all the main bodies, identity mutual recognition among all the main bodies is achieved, and an incidence relation is established; writing metadata required by the data provider or the data developer to publish data into a verifiable registry, and establishing a data space data ID of the metadata based on the data space main body ID of the data publisher and the metadata; connection is established among distributed digital housekeepers, an end-to-end encryption connection pipeline is formed, and encryption data exchange is completed based on a connection channel.

The disclosed embodiments involve recording performance metrics for network connections in a centralized database, storing network connection data in a global registry across multiple data centers, detecting backlogs at specific data centers linked to network elements and connections, and generating updated connection assignments. These assignments include identifiers for the involved data centers and connections. Upon receiving a connection assignment update notification, the method updates the network connection and communicates the first data center's connection state to the global registry.

Computer-implemented system for real-time validation and threat mitigation for structured health transactions, including: a client policy repository that contains client-specific validation rules, consent restrictions, and risk thresholds; a trusted policy execution enclave that only allows policies and models after remote attestation of code and configuration, and decrypts and processes protected fields exclusively within the enclave; a grammatically aware streaming validator that enforces format and semantic constraints and synthesizes an auto-repair suggestion in case of parser errors, transforming inputs into a policy-compliant form with minimal changes; a hybrid risk engine that calculates rule-based and learned risk scores and furthermore evaluates a subset of features using data protection-preserving calculations to determine risk contributions without decoding selected fields; a causal graph generator that correlates related transactions over time into an entity-resolved, time-aligned graph and identifies impossibility patterns with edge-wise responsibility values; a coordinator for federated learning who updates models from client-local aggregates under differential privacy budgets and suspends aggregation when a distribution drift above a policy threshold is detected; an audit subsystem that generates zero-knowledge evidence demonstrating that selected compliance predicates for a transaction have been met without disclosing protected health information; a risk-adaptive flow control system that directs high-risk substreams into micro-quarantine sections with enhanced testing while maintaining the basic service quality for low-risk substreams; and a register that stores a validity context mark which links each decision to the identity of the policies, models, scope of consent and runtime environment used.