46 results about "Identity resolution" patented technology

Identity nodes within bidirectional dual node hashchain (BDNH) bundles generate hash keys by processing partial metadata and linking them through identity graphs. Translation nodes perform identity resolution, data anonymization, and re-keying by transforming original identifiers into anonymous IDs and re-key IDs. Laplace noise enabler capsules introduce Laplace noise into translation layer logs for differential privacy. BDNHs share metadata between adjacent bundles for secure and efficient data transmission. A cognitive analytics layer shared among all bundles verifies hashed encrypted data packets using a gossip protocol for real-time validation. An analytics workspace layer activates re-key IDs and creates digital tags for datasets using BERT transformers, linking data through knowledge graphs. The system manages parallel processing and includes machine learning modules, homomorphic encryption, federated learning, zero-knowledge proofs, attribute-based encryption, and anomaly detection. Bundles' AI engines work with the Laplace noise enablers to analyze data, optimize noise, and enhance the data clean room functionality.

A system, method, and computer-program product includes receiving, from a third-party identity management system, an authentication response indicating a set of login attributes; obtaining, from an identity resolution service, a set of identity and authorization attributes using the set of login attributes, the set of identity and authorization attributes including a unique user identifier (UID); granting, by the identity resolution service, a session initiation token when the set of identity and authorization attributes satisfy predefined authorization criteria; in response to the identity resolution service granting the session initiation token: allocating a compute session and a persistent storage resource to the unique UID; executing, via the compute session, an operation that modifies files stored in the persistent storage resource; and transmitting, to a version control system, a version control operation that records the files modified in the persistent storage resource to a code repository using the unique UID or group identifiers.

A system and method for building first-party identity graphs using third-party data employs deep learning to enable privacy-preserving identity resolution. The system includes a deep learning model trained with transformer architecture and contrastive learning on a comprehensive third-party identity graph containing personally identifiable information (PII). Custom tokenizers process PII data by leveraging hierarchical structures and domain-specific characteristics to handle variations in spellings, abbreviations, and data formats. An identity matcher generates vector embeddings from first-party PII inputs, which are stored in a vector database for efficient similarity searches. A distributed similarity computation component compares first-party embeddings with third-party data embeddings, outputting similarity scores that enable fuzzy matching capabilities. A graph builder constructs accurate first-party identity graphs based on similarity thresholds while incorporating relevant third-party data.

This invention discloses a skeletonless, non-skeleton-dependent method for tracking similar small targets in UAV-based high-altitude overhead scenarios. Addressing the challenges of extremely low resolution, motion blur, and highly similar appearances of pedestrian targets in high-altitude aerial photography, which render traditional skeleton pose features ineffective, this method first dynamically calculates feature confidence by jointly evaluating the detection box size, detection confidence, and local sharpness. Based on this, it adaptively adjusts the fusion weights of spatial, appearance, and motion features in multi-source likelihood matching. Furthermore, to handle ambiguity regarding similar targets in congested scenes, it innovatively utilizes sharp displacements in a two-dimensional plane under UAV overhead views to construct motion pattern distinguishing factors (including direction and velocity consistency) to replace ineffective skeleton features and achieve accurate identity resolution. Finally, it combines multi-evidence fusion mechanisms such as spatiotemporal reachability, appearance consistency, and motion continuity to recover trajectories lost due to occlusion. This method effectively overcomes the feature instability and identity ambiguity problems of small targets under UAV high-altitude overhead views, significantly improving the robustness of target tracking in complex traffic scenarios.

A multi-component system for identity resolution and customer segmentation utilizes bitmap encoding to overcome storage and processing limitations of traditional approaches. The system comprises a bitmap encoding processor that associates binary strings with user identities in an identity graph, where each bit corresponds to a unique segment and indicates user membership through bit state. A metadata association table stores descriptive information for each segment and dynamically links to the encoding processor for automatic updates. The binary strings serve dual purposes as both segment representations and user identifiers, eliminating separate identifier systems. The system can be implemented as a software development kit and deployed across various hardware architectures, making previously cost-prohibitive large-scale segmentation operations computationally feasible.

A system and method for improving identity resolution match rates using deep learning techniques that enable privacy-preserving fuzzy matching of personally identifiable information (PII) employs a deep learning model trained with transformer architecture and contrastive learning on third-party identity graph data. Custom tokenizers process different Pll types by leveraging hierarchical structures and domain-specific characteristics. The trained model generates vector embeddings that enable fuzzy matching to account for variations in spellings, typographical errors, and data inconsistencies without requiring adherence to strict data schemas. A vector database stores embeddings for nearest neighbor searches to identify potential identity matches based on distance calculations between embeddings. A match filter applies logic to determine valid matches, and the system can operate without requiring movement of raw Pll data from secure environments.

Methods and systems are provided for evaluating edges of collapsed identity graphs for identity resolution. In embodiments described herein, a collapsed state of identity graphs, such as based on an identity namespace limit being exceeded by the identity graphs, is determined by applying an identity node and edge of an incoming record to the identity graphs. A temporary state of the identity graphs is determined by pruning edges of the collapsed state. A non-collapsed state of the identity graphs that includes the edge of the incoming record is determined by applying the edge of the incoming record to the temporary state. A different edge is determined to be pruned from the non-collapsed state as when the different edge is applied to the temporary state with the edge of the incoming record, the temporary state collapses into the collapsed state. An identity graph is updated based on the non-collapsed state.

A system and method for scalable vector search in identity resolution uses deep learning to enable privacy-preserving matching of personally identifiable information (Pll). The system employs a deep learning model trained with transformer architecture and contrastive learning on third-party identity graph data. Custom tokenizers leverage hierarchical structures and domain-specific characteristics. The trained model generates vector embeddings that enable fuzzy matching, accounting for variations in spellings, typographical errors, and data inconsistencies. A scalable vector database stores embeddings for efficient nearest neighbor searches to identify potential identity matches. A distributed similarity computation component searches the vector database and outputs potential matches based on vector similarity. A match filter applies predefined criteria to refine results.

The embodiment of the invention discloses an unauthorized attack detection method and device, a storage medium and electronic equipment. According to the method, the access request of the user and the response data of the target system are collected through the aspect program, the identity information of the user is identified through the identity analysis capability provided by the aspect program in the application layer, and the permission configuration information of the user is determined in combination with the permission configuration of the specific target system, so that the requirements of different permission logic scenes can be flexibly adapted; and the method has universality. Simulating a user role based on user identity information and permission configuration information by using the large language model in combination with the semantic understanding capability of the large language model, and judging whether an access request of the user and a response data text of a target system contain sensitive information with unauthorized behavior characteristics or not; the method does not need to depend on strong rule definition of sensitive data, and has very good implicit sensitive data identification capability. The unauthorized attack detection device, the storage medium and the electronic equipment in the embodiment of the specification also have the above beneficial effects.

This application discloses a method and system for dynamic mapping and scheduling of network resources based on identity resolution, relating to the field of computer network technology. The method includes: acquiring request information of the task to be scheduled, multi-source identity signals, resource node status, overall network load status, and service preference information; fusing and parsing the multi-source identity signals to construct a cross-domain unified identity identifier and generate an identity attribute vector; then, combining computing resource status, network link status, and service preferences, calculating the identity adaptability between the unified identity identifier and each resource node to generate a candidate resource node list; finally, making dynamic scheduling decisions based on overall network load and link status to determine the target resource node and its corresponding network path, and issuing network configuration rules and resource scheduling instructions. This achieves collaborative perception and dynamic matching of identity, network, and computing resources, improving the accuracy, real-time performance, and service adaptability of cross-domain resource scheduling.

A system and method for privacy-preserving identity resolution using deep learning enables accurate matching of personally identifiable information (PH) while maintaining data security. The system employs a deep learning model trained with transformer architecture and contrastive learning on third- party identity graph data. Custom tokenizers leverage hierarchical structures and domain-specific characteristics. The trained model generates vector embeddings that enable fuzzy matching, accounting for variations in spellings, typographical errors, and data inconsistencies. A vector database stores embeddings for nearest neighbor searches to identify potential identity matches. The system operates without requiring strict data schemas and supports flexible handling of future data variations.

The application provides a Bluetooth random address generation method and related electronic equipment. The method is applied to an electronic device including a Bluetooth Host and a Bluetooth module. The method includes: the Bluetooth Host generating an identity resolution key; in the case that the electronic device meets a first condition, the Bluetooth Host sending the identity resolution key to the Bluetooth module; the first condition is a condition for triggering the electronic device to reduce power consumption; the Bluetooth module generating a resolvable private address RPA based on the identity resolution key IRK and periodically updating the RPA based on the IRK; in the case that the Bluetooth Host is to perform Bluetooth service, the Bluetooth Host sending an RPA request to the Bluetooth module; the Bluetooth module sending the latest updated RPA to the Bluetooth Host; and the Bluetooth Host performing Bluetooth service based on the latest updated RPA.

A cognition-native semantic execution platform is disclosed, comprising a modular architecture for executing memory-bearing semantic agents across centralized, decentralized, and heterogeneous computing environments. The system includes interoperable layers for agent modeling, memory-native substrate transport, scoped trust zone governance, dynamic identity resolution, and runtime ethical enforcement. Semantic agents carry structured fields including intent, context, memory, policy references, mutation descriptors, and lineage, enabling persistent identity, traceable behavior, and ethically governed semantic mutation. Trust validation is performed via entropy-resolved behavioral slope authentication rather than persistent credentials. Execution is policy-scoped and auditable through agent-embedded lineage graphs and cryptographically signed policy references. The platform supports fallback propagation in stateless environments and operates independently of transport topology, enabling scalable, transparent, and ethically constrained reasoning across distributed systems.

The invention relates to the technical field of online transactions, in particular to a multi-dimensional task verification configuration method and system for identification analysis, and the method comprises the steps: recognizing the verification dimension type of a to-be-verified transaction task through analyzing the cross-chain scene and credit data dynamics of the to-be-verified transaction task; acquiring required verification configuration data according to the type; determining a corresponding dynamic reputation anchoring and cross-chain collaborative verification rule in combination with the dimension type; and when the matching relationship between the verification configuration data and the preset configuration standard meets the verification rule, completing multi-dimensional verification configuration. Wherein the preset configuration standard and the verification dimension type have a one-to-one correspondence mapping relationship. According to the method, scene self-adaption of the verification strategy is realized, the accuracy and efficiency of credit verification in a cross-chain environment are improved, dynamic and refined identity and credit management is supported, and the security and expandability of an online transaction system are enhanced.

An apparatus configured to process an indication of a wireless communication device with which the apparatus is allowed to perform a location finding operation, where the indication includes a first identity resolution key (IRK) unique to the wireless communication device; processing a payload including the announcement of the IRK; and comparing the IRK to a first IRK received by the always-on processor.

A method includes implementing, through a server of a Fifth Generation (5G) mobile network, a pseudo-Authentication Server Function (AUSF) component as a component of an architecture of a core mobile network of the 5G mobile network distinct from an existing AUSF module thereof executing on the server, and automatically routing a request for identity resolution of a User Equipment (UE) connectable to the 5G mobile network to the pseudo-AUSF component instead of the existing AUSF module, with the request including a concealed identifier of the UE. The method also includes automatically resolving the concealed identifier into a permanent identifier of the UE utilizing an existing Unified Data Management (UDM) module of the core mobile network based on communication between the pseudo-AUSF component and the existing UDM module, and automatically providing, through the existing UDM module and the pseudo-AUSF component, the permanent identifier of the UE to address the request.

A method of resolving an identity of an entity is disclosed. Entity data is ingested. Identity fragments observed in the entity data are recorded. All or a subset of identifiers that are connected across the identity fragments are discovered. A directed graph of the identity fragments is built. An entity profile is produced by applying a set of rules to the directed graph.

An electronic device is provided. The electronic device includes communication circuitry, at least one processor including processing circuitry, and memory including one or more storage mediums, storing instructions, wherein the instructions that, when executed by the at least one processor individually or collectively, cause the electronic device to receive, via the communication circuitry, an advertising packet advertised from an external electronic device, determine, based on a first list of identity resolving keys (IRKs) of other electronic devices whether a resolvable private address (RPA) of the external electronic device in the advertising packet is resolved, and based on determining that the RPA of the external electronic device is not resolved, request, from the external electronic device, via the communication circuitry, a version of a second list of IRKs.

A system and method for privacy-preserving identity resolution using deep learning enables accurate matching of personally identifiable information (PH) while maintaining data security. The system employs a deep learning model trained with transformer architecture and contrastive learning on third-party identity graph data. Custom tokenizers process data by leveraging hierarchical structures and domain-specific characteristics. The trained model generates vector embeddings that enable fuzzy matching, accounting for variations in spellings, typographical errors, and data inconsistencies. A vector database stores embeddings for nearest neighbor searches to identify potential identity matches. The system enables identity resolution without requiring Pll data movement from first-party environments. The invention facilitates building accurate first-party identity graphs and enables secure collaboration between parties without exposing underlying Pll data.

A computer-implemented method for maintaining unified guest identity records across heterogeneous hospitality data systems. The method receives guest interaction data from independent data sources operating on different schemas, normalizes identifiers through standardization algorithms, and applies two-stage matching comprising deterministic cryptographic hashing followed by probabilistic Bayesian inference. Core attributes are stored in a relational database with strong consistency guarantees while behavioral data is maintained in a document database with eventual consistency, synchronized through a change data capture mechanism providing near real-time synchronization. The identity resolution engine operates continuously in real-time, reducing storage requirements compared to systems allowing duplicate records. The system further implements a predictive segmentation model using online learning to adjust parameters in real-time while preserving accuracy for previously learned patterns. An event-driven workflow orchestration architecture records state-changing guest actions as immutable events and dispatches them to independent CRM, marketing automation, event management, and analytics modules that autonomously respond without centralized orchestration, enabling high-throughput processing with low latency.

This invention discloses a camera module identification method and system based on sensor OTP. The method includes: writing module identity information into the OTP storage area inside the image sensor; after the terminal device enters the running stage, the driver reads the module identity information stored in the OTP during the image sensor initialization process; after successfully reading the module identity information, the read module identity information is parsed to determine the module type; after completing the module identity parsing, the driver executes the corresponding initialization or configuration process according to the parsing result. This invention explicitly introduces the module identity information stored in the OTP inside the image sensor into the camera initialization and module identification process of the terminal device as the basis for system-level module differentiation, forming a module identification mechanism with embedded storage information as the core, and realizing system-level support for multi-module scenarios in a software manner.

A software development kit for providing targeted messages from a remote device to a client device through an app installed on the client device operates without any personal information leaving the client device. One or more Bloom filters are created and are mapped to specific app bundle identifiers. Matched identifiers are resolved against the set of Bloom filters to targeted messages based on user identifiers. Because the processing is performed locally on the client device, no personal information leaves the client device. Real-time measurement is performed by firing conversion events to an integrated mobile network, providing analysis of the effectiveness of the targeted messaging without providing any personal information to any remote device.

This application relates to a trusted communication identity resolution method and apparatus. The method includes: obtaining an identity token provided by a calling terminal when initiating a communication request; sending an identity credential request message to a ticket query server, the identity credential request message including the identity token; receiving the calling terminal identity certificate and resolution configuration information returned by the ticket query server in response to the identity credential request message, the resolution configuration information matching the calling terminal identity certificate; and resolving the calling terminal identity certificate based on the resolution configuration information to obtain the calling terminal identity information. It is evident that this application requires no modification to the client; adaptation can be achieved simply by configuring corresponding resolution configuration information for each different type of calling terminal identity certificate. This mechanism can quickly respond to the iterative needs of trusted communication services, shorten the development cycle for service adaptation, reduce the cost and difficulty of trusted communication system operation and maintenance, and promote the large-scale application and cross-scenario expansion of trusted communication technology.

A method for semi-automated adjudicated identity resolution comprising: seeking best match entity candidates via a core capabilities stage for the identity resolution wherein the core capabilities are called multiple times in parallel, providing differing subsets of the full inquiry indicia received from client, such that a large number of possible outcomes can be observed depending on which inquiry indica are used in combination with others; and assigning an initial outcome code for the resulting winner for each pass; wherein the initial outcome code may later be promoted or improved when considered in conjunction with the outcome of one or more other pass outcomes. Stewardship intent is monitored and, in the event an "accept" outcome is not initially found, the system recursively leverages the most positive results of prior attempts and generates additional passes in an effort to find a more acceptable outcome. Interim and eventual results are all experiential data and are captured for multiple uses including, but not limited to, tuning methods, input to Al methods for tuning, and informs downstream discovery and curation processes.

This invention provides an intelligent customer acquisition and automated marketing method based on multimodal behavioral sequences and causal gain attribution. The method includes: performing identity parsing, data cleaning and standardization, and data quality monitoring on the original event table to obtain a basic data table; processing the basic data table to obtain multimodal time series representations and user vector representations; constructing a causal gain attribution framework to obtain the true incremental contribution of a single user to a marketing action; performing cross-channel attribution and interpretability analysis to obtain attribution results; performing content representation and embedding, and content filtering to obtain personalized content recommendations; performing automated marketing orchestration and execution, as well as privacy protection and ethical risk detection; and finally, monitoring and evaluating the model. This invention enables unified representation of multimodal data, accurate attribution based on causal gain, automated cross-channel marketing orchestration, and privacy and ethical monitoring, significantly improving customer acquisition effectiveness, resource allocation efficiency, and decision-making transparency.

Techniques pertaining to enhancements to ranging and reporting in wireless communications are described. An apparatus (e.g., an initiator) performs a one-to-many contention-based ranging operation by: (a) generating a one-to-many initiator report; and (b) transmitting the one-to-many initiator report to a responder. The one-to-many initiator report contains a resolvable private address (RPA) hash calculated using an identity resolving key (IRK) of one of the responder.

An electronic device is provided. The electronic device may comprise a communication circuit, at least one processor including a processing circuit, and a memory storing instructions and including one or more storage media, wherein the instructions, when executed by the at least one processor, cause the electronic device to: receive, through the communication circuit, an advertisement packet advertised from an external electronic device; determine whether or not a resolvable private address (RPA) of the external electronic device within the advertisement packet is resolved, on the basis of a list of identity resolving keys (IRKs) of other electronic devices; and request a version of the list of IRKs from the external electronic device through the communication circuit, on the basis of determining that the RPA of the external electronic device is not resolved.

The invention relates to the technical field of image processing, and discloses an information verification result generation method and device based on edge calculation, computer equipment and a storage medium, and the method comprises the steps: collecting to-be-recognized identity identification information through a preset edge calculation model, and generating a target identity ID; and analyzing the target identity ID, and verifying the target position information and the target physiological information to generate a target information verification result. Through the mode, the biological characteristic information is used as a core basis of identity recognition, so that the livestock information cannot be forged or replaced, and the identity of the livestock is judged by comparing the biological characteristics. According to the method, image acquisition and feature extraction are completed through an edge calculation model, target position information and target physiological information are generated by analyzing a target identity ID, and a target information verification result is further generated through automatic verification. The method can be applied to the field of agricultural insurance business, and the reliability of a risk management system for identifying fraud risks is improved.

A system and method for efficient identity data matching using compressed mapping indexes generates an identity mapping index that consolidates identity mapping relationships from multiple sources into a compact, binary-encoded structure where source identifiers are mapped to integer values representing the presence or absence of mappings across multiple partners. Data is processed through identity resolution to generate both derived identifiers (generated directly from input data) and maintained identifiers (linked to a persistent identity graph). The system performs matching operations against identity mapping indexes using derived-only identifiers and derived-plus-maintained identifiers separately, then compares results to quantify the performance improvement from identity graph-based resolution. The compressed index structure significantly reduces storage requirements and enables rapid join operations. The system includes data ingestion modules supporting multiple transfer protocols, identity resolution pipelines, matching engines, statistics generation modules, and security controls for data deletion after processing.