5474 results about "Third party" patented technology

A system and method of calculating an estimated time of arrival for a traveler is provided, along with a notification of this estimated time that is sent to a third party. The traveler is equipped with a navigation unit having a global positioning sensor and a wireless communications device. The navigation unit communicates with a service center equipped with a server capable of generating a preferred navigational route for the traveler. The service center also includes a traffic database for maintaining current traffic information. Once the traveler has selected a predetermined time and frequency of notifications based upon a selected criterion, the navigation unit transmits the traveler's position and velocity to the service center. The service center then calculates the estimated time of arrival based upon the traveler's position, velocity, distance to be traveled and traffic and weather conditions. Once this time is calculated, the service center sends a notification to the third party.

The invention discloses an intelligent operation and maintenance management and control system for an information communication network, and belongs to the technical field of communication. The system comprises the following modules: an intelligent sensing and data acquisition module which is responsible for real-time acquisition of multi-source network data, dynamic monitoring of cross-domain equipment states and conversion of heterogeneous data into a unified standard; the network intelligent analysis module integrates network performance prediction, fault risk assessment, abnormal behavior identification and security threat monitoring, and provides comprehensive network operation and maintenance insight; the intelligent resource scheduling module is used for realizing dynamic allocation of cross-domain network resources and ensuring efficient and safe utilization of the resources through multi-dimensional optimization and a real-time load balancing strategy; the intelligent decision support module is used for continuously optimizing an operation and maintenance strategy based on machine learning, analyzing a long-term operation trend and providing suggestions for management decisions; and the open integration and collaboration module provides integration of an open API interface and a third-party system, supports cross-domain collaboration management, and improves the flexibility and expansibility of the system.

The invention discloses a cross-industry data security sharing method and system based on data desensitization and a medium, and relates to the related field of privacy computing, and the method comprises the following steps: carrying out dynamic desensitization processing on original data, generating a shared data set for real-time recording, constructing an access behavior characteristic spectrum to configure a dynamic access strategy, and establishing a third-party security data sharing platform, storing the shared data set in a trusted execution environment in a fragmented manner, obtaining fragmented encrypted data, executing a dynamic access strategy, performing conjoint analysis on the fragmented encrypted data through a security multi-party computing protocol, and generating a data security sharing suggestion. The technical problems that in cross-industry data sharing, the privacy leakage risk is high, the static desensitization rule is rigid, and the multi-party calculation efficiency is low are solved, and the technical effects of breaking data islands and constructing safe and mutual-trust data circulation ecology through fusion of dynamic hierarchical desensitization and a trusted execution environment are achieved.

The present invention discloses a third party registration processing method based on the IMS network, which comprises that a UE completes the registration on a S-CSCF entity; the S-CSCF entity starts a waiting timer; the UE and a P-CSCF entity initiate and complete a registration status subscribing respectively to the S-CSCF entity; the S-CSCF entity initiate a third party registration to an AS when the waiting time of the waiting timer is enough. Through the present invention, the S-CSCF entity performs a waiting after the UE is successfully registered, to make the subscribing success of the registration status of the P-CSCF and the UE take precedence over the third party registration and avoid the situation of conflicting data of the UE, the P-CSCF, the S-CSCF and an HSS, to make the UE, the P-CSCF and the S-CSCF effectively process the abnormal circumstance occurred when the third party registration fails.

Systems, methods, and computer-readable storage media for compliance verification and validation of cyber resilience in a distributed entity or third-party network (DETPN). Some methods can include generating or identifying, by one or more processing circuits, one or more compliance parameters for a plurality of entities or third-parties on the DETPN. Some methods can include determining, by the one or more processing circuits, at least one compliance level. Some methods can include receiving or identifying, by the one or more processing circuits, environmental data of the DETPN. Some methods can include determining, by the one or more processing circuits at a second timing phase, an updated at least one compliance level for at least one of the plurality of entities or third-parties based at least on the environmental data. In some implementations, some methods can include generating and storing, by the one or more processing circuits, one or more tokens.

The present invention introduces a universal AI-powered pet management platform that establishes an entirely new category of technology, transcending conventional pet training systems. This comprehensive system integrates a modular wearable pet device with interchangeable sensors, sophisticated AI processing capabilities, and diverse output modules to create a unified ecosystem for holistic pet care. Unlike traditional training devices focused solely on behavior modification, this platform simultaneously manages multiple domains including real-time health monitoring, environmental safety assessment, emotional well-being analysis, autonomous training, emergency response, and seamless integration with external systems. The platform's universal architecture enables dynamic adaptation across diverse applications from companion animals to service animals, wildlife monitoring, and specialized deployments. By leveraging advanced artificial intelligence models, multimodal communication pathways, and a universal API for third-party integration, the system creates an interconnected technological framework that fundamentally transforms the relationship between pets, technology, and human interaction, rendering isolated pet devices obsolete.

Systems, methods, and / or computer readable storage media for protecting data. A system can include one or more processing circuits configured to receive or identify at least one token including cyber resilience data of at least one entity and corresponding with at least one posture or compliance parameter of at least one third party The one or more processing circuits can perform a zero-knowledge proof (ZKP) on the cyber resilience data, determine at least one posture or compliance parameter of the at least one third party is satisfied based on the cyber resilience data, and / or generate at least one ZKP including at least one cryptographic commitment obfuscating the cyber resilience data. The one or more processing circuits can provide, to at least one third party computing system of the at least one third party, the at least one ZKP or indication of performance of the at least one ZKP.

The invention relates to the technical field of data processing, provides a multi-node carbon emission intelligent contract verification method based on a block chain, and aims to solve the problems that data verification in an existing carbon asset transaction system is non-transparent, high in trust cost and difficult to adapt to policy changes. Distributed storage and dynamic verification of data are realized by constructing a hierarchical block chain architecture, the data are collected by using edge computing nodes, and third-party verification data are obtained through an oracle machine node cluster. The dynamic rule engine monitors data changes in real time, triggers a multi-stage verification process, and improves the data accuracy. And meanwhile, an improved Byzantine fault-tolerant mechanism is adopted to reach a consensus, and the system has the functions of strategy dynamic updating and security enhancement, so that the flexibility and security of the system are improved. According to the method, multi-party consensus and real-time verification of the carbon emission data are realized, trust cost of cooperation among enterprises is reduced, and healthy development of a carbon emission permit trading market is promoted.

A system and method for facilitating collection of Road User Charges (RUC) using a digital currency within a Distributed Ledger Technology (DLT) network are disclosed. The system generates secure digital wallets for Road Users and Facility Owners, receives trip, position, distance, and cost data from vehicles, sensors, and facility systems, and encodes settlement logic into smart contracts. These contracts automatically execute jurisdiction-specific disbursements across blockchain, directed acyclic graph (DAG), or hashgraph frameworks, ensuring scalability and auditability without reliance on centralized tolling infrastructure. An AI Activity Module processes multi-source telemetry—including vehicle sensors, GNSS / PNT data, roadside infrastructure, and third-party traffic feeds—to detect congestion, forecast conditions, optimize routing, and dynamically adjust segment-level RUC pricing in real time. The integration of AI-driven adaptive pricing with distributed ledger settlement provides a decentralized, infrastructure-agnostic framework for secure, transparent, and verifiable road use fee collection across multiple jurisdictions, distinct from conventional tolling systems.

The invention relates to the technical field of digital information transmission, and provides a communication network security situation prediction method and system based on big data, which break through the limitation of single data in the aspect of data fusion, integrate four large classes and 12 subclasses of multi-source heterogeneous data, and combine a dynamic weighting mechanism to make feature extraction more comprehensive and accurate; on the aspect of model architecture, CNN-Bi-LSTM-Attention three-level fusion and PSO optimization are adopted, spatial and temporal features are effectively captured, the convergence speed is increased, the prediction accuracy is high, and the false alarm rate is low; in the risk assessment aspect, a layered assessment system is constructed, and early warning is realized in combination with a dynamic threshold value and Monte Carlo simulation; the model training module innovatively adopts a federated learning mode, and the model generalization ability is improved while data privacy is guaranteed; the prediction analysis module deploys an optimization hybrid model, supports high-concurrency prediction and is short in response time; the visual decision-making module provides three-dimensional visualization and geographical drilling functions, and output data can be seamlessly connected with a third-party platform.

Various systems and methods are described for obtaining compensation for tasks performed by a humanoid robot, where the humanoid robot is associated with a first party. The method includes a first party providing a humanoid robot for use in an operating location. The humanoid robot engaged in performing a plurality of tasks at the operating location. A third party compensates the first party with a specified amount of currency for a pre-determined time interval during which said humanoid robot has engaged in performing the plurality of tasks at the operating location.

The invention relates to a federated learning system based on multi-key homomorphic encryption and adaptive differential privacy, and belongs to the technical field of privacy computing. According to the system, on the premise that no trusted third party exists, a multi-client collaborative key generation and threshold decryption mechanism is achieved, it is ensured that model parameters are always in an encrypted state in the aggregation process, and leakage of a single node is prevented. By introducing a parameter sensitivity analysis and selective encryption strategy, the system only encrypts high-risk parameters, and the encryption burden is effectively reduced. Meanwhile, in combination with an adaptive privacy budget allocation mechanism, the system dynamically adjusts noise intensity according to a model training state, and model performance and convergence speed are maintained while privacy protection capability is improved. According to the method, high robustness and collusion resistance are realized, stable operation under the condition that part of clients are offline is supported, and the method is suitable for application scenes such as medical treatment and finance with high data sensitivity and strict performance requirements.

The present disclosure describes systems and methods for detecting and preventing data misconfigurations within a security-focused data fabric platform. The system integrates an advanced script migration engine designed to streamline the translation of security rules and scripts across different scripting languages while ensuring alignment with the fabric's unified schema. The method involves receiving inputs from data sources, mapping these inputs to entities of a target schema, monitoring real-time data changes, and simulating impacts on operational dependencies to detect misconfigurations proactively. Leveraging AI-driven mechanisms, including Large Language Models (LLMs), the system dynamically identifies breaking changes in third-party data streams, issues alerts, and provides suggested fixes. The script migration engine further enhances the platform's functionality by automating cross-platform script translations and enabling faster onboarding of security tools. Together, these innovations ensure scalable, accurate, and resilient integration and management of security data across heterogeneous sources, strengthening operational integrity and minimizing security risks.

The disclosure belongs to the technical field of network security, and provides a method for constructing a feature knowledge base of mapping behavior based on deep learning, which includes: data acquisition and preprocessing: extracting five-tuple information and behavior features from network traffic. The disclosure automatically extracts the spatio-temporal features through the deep learning model, and enhances the sensitivity to abnormal behaviors by combining the attention mechanism, thus significantly improving the detection accuracy. The explanatory AI technology is used to automatically generate detection rules, the maintenance cost of manual rules is greatly reduced and the efficiency of rule generation is significantly improved. The feature knowledge base supports dynamic updating, may integrate third-party threat information in real time, and ensures the continuous defense ability against new attacks and variant detection means.

Systems, methods, and devices to detect unauthorized third-party connections within a network infrastructure, such as by analyzing network traffic data using fuzzy matching and machine learning techniques. One aspect includes receiving network traffic data comprising records of communication events involving network identifiers, determining communication relationships between network entities identified by the network identifiers, accessing entity identifiers associated with known third-party systems, and determining associations between the network identifiers and the entity identifiers using a fuzzy matching process. Other aspects include identifying communication relationships involving the third-party systems based on the associations and detecting unregistered or unknown third-party connections within the network infrastructure. Further aspects include normalizing identifiers, computing string similarity metrics, assigning confidence scores, incorporating external data sources, building network association patterns, comparing current patterns to baseline patterns to detect anomalies, and updating security policies or firewall rules in response to detected anomalies. Additional aspects are provided.

The invention discloses a commerce and trade circulation supply chain optimization method based on multi-modal data fusion, and the method comprises the following steps: 1, multi-modal data collection: collecting the multi-modal data of the whole supply chain in real time through an Internet of Things device, an enterprise ERP system, a logistics tracking system and a third-party platform, the multi-modal data comprises text data, image data, voice data, time sequence data and spatial data. When the scheme is implemented, multi-source heterogeneous data of the Internet of Things, ERP and the like are integrated, so that the problem of an information island in a traditional supply chain is effectively solved; position coding and a cross-modal attention mechanism are introduced into the multi-modal fusion model, so that the data alignment precision is remarkably improved, for example, when'emergency order adding 'in a voice communication record is associated with a corresponding order image, the weight distribution accuracy is improved; the application of the block chain technology ensures the transparency and traceability of the supply chain decision.

Systems, methods, and computer-readable storage media for providing a composable cyber resilience object. A method can include identifying, by one or more processing circuits, a posture state of at least one entity, generating or selecting a first plurality of code blocks corresponding with a parameters of at least one third-party, and determining the entity qualifies for protection based on the posture state and the rules or conditions. The method can include generating or selecting a second plurality of code blocks including functions to provide the protection based on the rules or conditions and generating the composable cyber resilience object by integrating a portion of the first plurality of code blocks and the second plurality of code blocks into at least one data structure. The method can include linking the composable cyber resilience object and a computing or networking infrastructure of the entity using a communication interface or structure.

The invention discloses a verifiable medical data query method based on a DAG block chain architecture, and belongs to the technical field of block chains and medical information management. According to the method, medical events such as diagnosis and treatment records and image reports are modeled into DAG nodes, an on-chain topology with time sequence and causal association is constructed by encrypting a hash pointer, dynamic indexing and multi-keyword verifiable query are achieved in combination with an off-chain authentication data structure, a verification object containing a matching node set and a verification path is received, and the verification object is subjected to dynamic indexing and multi-keyword verifiable query. The authenticity, integrity and timeliness verification of the result is independently completed based on the authentication root stored on the chain without depending on a third party. According to the method, through an on-chain and off-chain collaborative storage and incremental authentication updating mechanism, on the premise of ensuring privacy and tamper-proofing of medical data, query efficiency, verification performance and expandability under high concurrency are remarkably improved, communication and resource expenses are lower, and the method is suitable for large-scale popularization and application. The method is suitable for application scenes such as cross-institution medical data sharing, remote diagnosis and treatment and compliance auditing.

A system and method for real-time, identity-free personalization using deformable emotional trait vectors to dynamically adapt digital and voice-based experiences. Each user session is modeled as a behavioral object known as a Vectra, composed of fluidic traits—such as mass, viscosity, temperature, volatility, and texture—that evolve continuously in response to live behavioral, contextual, environmental, and voice-derived signals. These Vectras traverse a dynamically warped emotional space, the Vectraverse, influenced by ambient conditions including time of day, noise level, inventory urgency, and engagement rhythm. Gravitational pull toward predefined emotional goal attractors modulates system behavior, while a goal mutation engine reclassifies session intent when confidence decays or friction spikes. Outputs include tone modulation, content pacing, offer framing, and gamified reward logic—all executed without storing identity, login credentials, or historical profiles. The system supports modular deployment across voice, screen, signage, mobile, and in-room environments, and integrates with large language models, AI agents, and third-party personalization stacks via privacy-safe APIs and federated learning. Designed for zero-ID personalization, the platform enables emotionally intelligent, context-aware engagement across any surface or session.

The invention discloses an order-driven cross-factory collaborative production system, and relates to the technical field of intelligent manufacturing and supply chain collaboration, and the system obtains the productivity data, logistics cost and tax policies of a plurality of production bases such as Ningbo, Thailand and America in real time, and carries out the intelligent splitting and distribution of orders through a multi-base productivity game algorithm. And dynamic optimal matching of the order and the productivity is realized. Meanwhile, the system integrates WMS inventory data and third-party logistics real-time quotation, a transportation scheme with the lowest total cost is generated by adopting a genetic algorithm, and cross-border logistics and tax expenditure are remarkably reduced. The system overcomes the problems of information isolated island, response lag, extensive cost control and the like in traditional multi-factory production, realizes global productivity collaborative optimization and supply chain integrated intelligent decision, and improves the enterprise order performance efficiency and the overall resource utilization rate.

Various systems, computer-readable media, and computer-implemented methods of providing improved data privacy, anonymity and security by enabling subjects to which data pertains to remain “dynamically anonymous,” i.e., anonymous for as long as is desired—and to the extent that is desired—are disclosed herein. Embodiments include systems that create, access, use, store and / or erase data with increased privacy, anonymity, and security—thereby facilitating the availability of more qualified and accurate information. When personal data is authorized by data subjects to be shared with third parties, embodiments described herein may facilitate the sharing of information in a dynamically-controlled manner that also enables the delivery of temporally-, geographically-, and / or purpose-limited information to the receiving party. In one example, the disclosed techniques may be used to functionally separate geospatial information, such that it remains “dynamically anonymous,” i.e., anonymous for as long as is desired—and to the extent or degree that is desired.

Systems, methods, and computer-readable storage media for compliance verification and validation of cyber resilience in a distributed entity or third-party network (DETPN). Some methods can include generating or identifying, by one or more processing circuits, one or more compliance parameters for a plurality of entities or third-parties on the DETPN. Some methods can include determining, by the one or more processing circuits, at least one compliance level. Some methods can include receiving or identifying, by the one or more processing circuits, environmental data of the DETPN. Some methods can include determining, by the one or more processing circuits at a second timing phase, an updated at least one compliance level for at least one of the plurality of entities or third-parties based at least on the environmental data. In some implementations, some methods can include generating and storing, by the one or more processing circuits, one or more tokens.

The invention relates to the field of enterprise industry chain evaluation, and discloses an artificial intelligence-based enterprise industry chain multi-dimensional evaluation system and method, and the system comprises a data collection module which is used for obtaining industry chain data from a structured database, an unstructured text and a third-party platform; the data fusion module is used for constructing a dynamically updated industrial chain knowledge graph through a natural language processing technology; the multi-dimensional evaluation module comprises a financial health evaluation sub-module, a supply chain toughness evaluation sub-module, an innovation power evaluation sub-module and a carbon emission evaluation sub-module, and each sub-module generates quantitative scores by adopting an LSTM neural network, a PageRank algorithm and a space-time diagram convolutional network model and weights the quantitative scores to obtain comprehensive scores; the risk early warning module is used for simulating a triple conduction effect of an external event on an industrial chain based on a graph neural network and generating a risk index and a coping strategy; and the visual interaction interface dynamically displays the evaluation result. According to the method, the problems of data splitting and poor dynamic adaptability in a traditional evaluation method are solved, and accurate evaluation of the industrial chain is realized.

A method, apparatus, and system of activating and using a contactless card via unique activation codes are disclosed. A system includes a memory and a processor configured to: receive an account number for a contactless card from a third party computing system; generate a card activation code for the contactless card, the card activation code being unique to the contactless card; generate a customer-specific uniform resource locator (URL) by appending the card activation code to a general URL, the general URL being associated with an entity of the system; transmit the customer-specific URL to the third party computing system with instructions to write the customer-specific URL into a wireless chip of the contactless card; associate the card activation code with the account number and information regarding a customer associated with the contactless card; and store the card activation code within the memory to be referenced during activation.

Various aspects of the disclosure relate to enforcing dynamically updated network security policies in real-time (or upon an identified update) from multiple organizations and anonymously analyze computing system configuration information uploaded from third-party computing systems. An analysis engine monitors compliance information and compare the compliance information against the security rules and / or requirements for one or more enterprise networks. A visualization providing a network map with a visual representation of each product system service system may include communication links between internal applications and / or computing systems and drill-down capability to identify issues as they are occurring or are predicted to occur. The security escrow system may include a mechanism to automatically enable / disable access between third party networks and one or more enterprise computing systems in real-time based on identified compliance information.

The invention relates to the technical field of information authentication management, and discloses an information processing method and system based on authentication and admission assessment, and the method comprises the steps: achieving the automatic extraction of key index data in enterprise registration information and data information based on an OCR technology, and carrying out the consistency verification of the relation between the two, and obtaining a verification result; the authenticity and integrity of submitted information are ensured; then, the system performs difference field marking in combination with third-party registration information and index data, and accurately identifies data inconsistent items; performing quantitative risk scoring based on the index data, and dynamically determining an auditing queue to which the enterprise belongs; finally, the risk score and the difference field marking result are integrated to judge whether to trigger a manual auditing process or not, approval, filing and storage are automatically completed for enterprises needing to be audited, closed-loop automatic management from information collection and verification to risk assessment and approval is achieved, and the authentication efficiency and risk control accuracy are remarkably improved.

Systems and methods disclosed herein automatically authorize, audit, and manage usage of protected digital content via agentic artificial intelligence (AI) models. A data access / usage request is received (e.g., from a graphical user interface) that is associated with digital assets licensed from third parties. The system uses a first AI agent set to identify the digital content and retrieve corresponding access policies from a distributed database. The system uses a second AI agent set (same as or different from the first AI agent set) to evaluate the request against the retrieved policy to generate a permission set and / or settlement instructions. The system uses a third AI agent set (same as or different from the first and / or second AI agent sets) to embed digital watermarks and / or cryptographic signatures into the accessed content, and to record an audit trail of access, authorization, and / or settlement events in a distributed ledger or database.

The invention discloses an industrial communication protocol conversion system and conversion method. The method comprises the following steps: acquiring data of an industrial communication source protocol; protocol conversion: converting the source protocol data into target protocol data according to a sequence of protocol analysis, standardized modeling and protocol repackaging; according to protocol analysis, original data transmitted from different hardware interfaces are analyzed according to corresponding industrial protocols; the standardized modeling parses the data into a data model in a unified format; protocol repackaging: recoding the data model into a data frame conforming to a communication specification according to a target protocol rule; and data output: pushing the obtained target protocol data to a third-party server through an MQTT protocol or directly storing the target protocol data in a database for a third-party system to access. Through three core technologies of protocol analysis, unified data modeling and protocol packaging, lossless conversion among different industrial protocols is realized, and an efficient and reliable data communication infrastructure is provided for an industrial automation system.

The invention discloses an advertisement putting strategy optimization method and system based on preference data collaboration, and relates to the technical field of advertisement putting, and the method comprises the steps: collecting the internal user data of a local advertisement putting platform, obtaining the external user data of a third-party platform through a safety data interface, carrying out the integration and preprocessing of the data, and obtaining an advertisement putting strategy; extracting explicit preference data and implicit preference data; a user-advertisement scoring matrix is constructed based on the preference data, and user preference vectors are generated after decomposition; acquiring copywriting text, image and category information of an advertisement to be put, constructing an advertisement feature expression model and generating an advertisement feature vector; calculating a matching degree score based on the user preference vector and the advertisement characteristic vector, and dynamically optimizing an advertisement putting strategy according to the score; according to the method, through comprehensive utilization of explicit and implicit preferences of the user, more accurate user interest modeling and advertisement matching are realized, and the advertisement putting effect and putting efficiency are effectively improved.

Methods and systems for generating a sharable model splice of a digital engineering (DE) model are provided. The method comprises receiving a DE model file in a native file format; extracting model data; storing the model data in a storage area; generating external, commonly-accessible splice functions that enable external access to digital artifacts derived from the model data; and generating the sharable model splice, which comprises access to a selective portion of the digital artifacts, and access to at least one of the splice functions. The splice functions provide addressable API or SDK endpoints that enable access by third-party applications and users to the digital artifacts without access to an entirety of the DE model file and without requiring direct engagement with a DE tool associated with the DE model type. These endpoints also provide a unified programming interface to sharable model splices generated from DE models.