912 results about "Biometric data" patented technology

The invention provides a method and system for preventing identity spoofing during digital authentication processes using artificial intelligence (AI)-driven pattern recognition. The system receives an input data stream from a user attempting to authenticate, which may include biometric data, device behavior data, or user interaction data. An AI-based pattern recognition model processes this data to analyze user behavior patterns and detect any anomalies that may indicate potential spoofing attempts. The system compares the processed data against a pre-established user profile to generate an authentication decision. If anomalies are detected, the system can flag the authentication for further review or trigger additional verification steps, such as multi-factor authentication (MFA) or one-time password (OTP) prompts. The system continuously learns from user interaction data and dynamically updates the user profile to improve the accuracy of identity verification.

The invention relates to the technical field of computer security, and discloses a computer remote login identification device based on artificial intelligence, which comprises a user side device module used for collecting biological identification data and input behavior data of a user; the authentication and verification module is used for executing multi-mode identity authentication and dynamically adjusting an authentication strategy; the behavior analysis and risk assessment module is used for analyzing a behavior mode and a login environment of the user; the database and storage module is used for storing user identity information, behavior characteristic data and authentication logs; and the security monitoring and alarming module is used for monitoring the login activity of the user in real time and detecting potential security threats. According to the invention, the design based on multi-modal authentication greatly improves the security of remote login. By combining a plurality of authentication means such as face recognition, fingerprint recognition and voice recognition, the system can effectively prevent security vulnerabilities such as password stealing, fingerprint counterfeiting or facial image attack.

Bending data is used to facilitate tracking operations of an extended reality (XR) device, such as hand tracking or other object tracking operations. The XR device obtains bending data indicative of bending of the XR device to accommodate a body part of a user wearing the XR device. The XR device determines, based on the bending data, whether to use previously identified biometric data in a tracking operation. A mode of the XR device is selected responsive to determining whether to use the previously identified biometric data. The selected mode is used to initialize the tracking operation. The selected mode may be a first mode in which the previously identified biometric data is used in the tracking operation or a second mode in which the previously identified biometric data is not used in the tracking operation.

The invention relates to the technical field of intelligent decision making, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a multi-modal data-based event analysis method, which comprises the following steps of: obtaining attribute data, monitoring data, environment data and biological characteristic data of a user, and performing standardization processing on the attribute data, the monitoring data, the environment data and the biological characteristic data; combining semantic analysis and structured fusion of the text records to form a unified input data set; and performing multi-modal fusion modeling on the unified input data set by using an intelligent decision model, generating a potential event analysis result of an individual state, generating a visual report containing potential event levels, main influence factors and intervention suggestions based on the result, and finally sending the report to a user terminal. According to the method, the multi-source structured data and the multi-source unstructured data are integrated, and the intelligent decision-making model is introduced to realize feature level fusion and semantic enhancement modeling, so that the accuracy and timeliness of individual state analysis are effectively improved, and the personalized expression of an analysis result is enhanced.

The invention relates to an intelligent dialogue system and method based on an AI multi-mode large model. The method comprises the following steps: collecting biological characteristic data of a user in real time; cloning a personalized expression mode of the user by using the generative adversarial network; driving the audio avatar to perform multi-round dialogue interaction with the user, capturing a real-time physiological signal of the user through an expression recognition module, and generating a dynamic response content suggestion in combination with a dialogue context; and analyzing the interaction process based on the reinforcement learning model. The multi-modal deep fusion of the voice rhythm features, the language structure features and the facial dynamic features is realized, so that the limitation of single-modal or simple feature splicing in the prior art is broken through, the emotional state of the user can be accurately and comprehensively captured, the intention is expressed and the fine physiological reaction is expressed, and the user experience is improved. And a solid foundation is laid for constructing high-fidelity user representation.

According to various embodiments, a system and method for verifying a user's identity using both document-based and biometric data is disclosed. The system may prompt a user to upload an image of a government-issued identification document and extract user information from the image using optical character recognition (OCR). The system may also extract the embedded face image from the ID and prompt the user to take a real-time selfie while performing one or more randomized actions or poses. A facial recognition engine may compare the extracted ID image to the live selfie to determine a similarity score. Based on this match, along with optional document authenticity checks, the system may confirm the user's identity in real-time for use cases such as account access, onboarding, and regulatory KYC compliance.

The invention relates to the technical field of computers, in particular to a multi-modal model fusion-based water decision-making system, which comprises a virtual digital human interaction module, an intelligent agent business middle table and a large model technology base, and is characterized in that the virtual digital human interaction module is used for monitoring a voice instruction of a user; the method comprises the following steps: acquiring a voice instruction of a user, acquiring biological characteristic data of the user by using a multi-modal sensor, identifying relevance characteristics between the voice instruction and the biological characteristic data through a water conservancy emergency scene emotion identification model, acquiring indication information, and sending the indication information to an intelligent agent service middle station; the agent business middle platform performs task chain analysis on the indication information based on a water conservancy professional term intention recognition model to obtain different task requirements, and calls a large model technology base to make a decision based on the different task requirements to obtain decision information; a water conservancy large model trained based on a domain mechanism model library is integrated on the large model technology base. According to the invention, more efficient and intelligent services can be provided.

A system and method (400, 600, 700, 900, 1100, 1200) of verifying an originator of an object using a biometric operation can include the steps of requesting (400, A) a biometric certificate from an enrollment service, capturing and receiving (400, C, D) a biometric reading associated with a user, transforming (400, E, F, G) the biometric reading into a format that can be made public, and creating (400, I, J) a user's certificate containing the public biometric data.

Examples relate to a fatigue detection system to monitor and assess pilot fatigue levels during flight operations. An example system includes a wearable biometric sensor (WBS) integrated into a wristband that captures biometric data from the pilot. A processor analyzes the captured data to determine the pilot's fatigue level. When this level exceeds a predetermined threshold, the system provides an alert to the pilot through a haptic feedback mechanism in the wristband. Additionally, the system generates personalized fatigue mitigation advice, which is displayed on an electronic flight bag (EFB) application accessible to the pilot. The advice may include recommendations for taking a controlled rest, consuming caffeine, or engaging in physical activity. The system enhances flight safety by providing real-time alerts and actionable advice to combat pilot fatigue.

The invention relates to the technical field of intelligent security and protection, and discloses an identity authentication method integrating AI and password technologies. According to the method, biological characteristic data are collected through a multi-mode biosensor, and the biological characteristic data are encrypted after being processed by a deep convolutional neural network. And training an identity authentication model by using a federated learning framework in combination with a differential privacy technology, and carrying out distributed verification. And generating a one-time dynamic password based on a verification result, binding the one-time dynamic password with spatio-temporal characteristics of user behaviors to construct a matrix, and controlling the access authority by adopting an attribute-based encryption algorithm. The system is also provided with an abnormal behavior detection model, a dynamic identity label updating mechanism, a secret key updating strategy and a multi-factor authentication decision engine. The method improves the security and accuracy of identity authentication, realizes fine authority management, and is suitable for the field of intelligent security and protection.

A system and method for generating patient care instructions based on real-time sensor and medical data. The method includes receiving time-stamped sensor data from a sensor network comprising motion, occupancy, and environmental sensors, and receiving medical data associated with a patient, including medical conditions, treatment history, medication data, and biometric data. The sensor data is enriched with room-specific information, and activity pattern data is generated in real time using a pattern recognition model. The activity pattern data includes mobility, sleep patterns, medication adherence, statistical measures, temporal patterns, and correlations with medical data. Anomalies indicating potential health risks are detected by comparing current activity patterns with baseline data. A prediction model, trained on historical patient data, assesses the patient's health and generates care instructions accordingly. The care instructions are securely delivered to patient devices, caregiver applications, or automated medication dispensing systems, enabling timely interventions and continuous patient monitoring.

Systems and methods for performing zero knowledge proofs to prove a user's possession of secret data and / or biometric data without exposing such data. The methods can include receiving a certificate signing request and biometric data associated with a user; creating a stable key based at least in part on the biometric data; creating a private key based at least in part on the stable key; transmitting the private key to the user device for local storage thereon; creating a public key based at least in part on the private key; and forwarding the certificate signing request to an issuer.

The invention relates to the technical field of artificial intelligence and biological characteristic analysis, in particular to an AI-based personalized postpartum rehabilitation medical beauty evaluation system and method. The method comprises the following steps: generating a standardized action sequence according to a rehabilitation stage and a historical record of a user and guiding execution; collecting dynamic biological characteristic data in real time; aligning data and distributing dynamic weights by using a multi-modal fusion model guided by time sequence semantics, constructing a three-dimensional response graph by combining a tension response function, a collaborative exponential function and a stable fluctuation function, and generating individual embedded vectors through a graph neural network; identifying a potential high-risk time period through map potential energy offset analysis and disturbance sensitivity factors; integrating a user state, a historical response and an intervention knowledge graph, recommending a dynamically adaptive intervention scheme by using a multi-channel attention network, and continuously optimizing through a feedback closed loop; precise evaluation and personalized intervention recommendation of the postpartum rehabilitation process are realized through multi-modal fusion and dynamic modeling, and the rehabilitation efficiency and safety are improved.

The invention relates to the technical field of additive manufacturing, and discloses an additive manufacturing lens surface optimization method based on real-time feedback control. The method comprises the following steps: firstly, acquiring eye biometric data and personalized visual demand parameters of a wearer, establishing a personalized optical model of eyeballs according to the eye biometric data and the personalized visual demand parameters, and deducing a retina defocusing amount distribution map; and determining spatial arrangement and geometric morphology parameters of the distributed out-of-focus microstructure layer on the lens according to the atlas. In the additive manufacturing process, the optical material is deposited and solidified layer by layer, and the three-dimensional shape information of the surface of the optical material is obtained in real time after deposition of each layer. And comparing and analyzing the morphology information with a theoretical model to generate a morphology deviation result. And then, a correction instruction of the printing parameters is calculated by using the correction model, and the printing parameters of the additive manufacturing equipment are adjusted in real time, so that real-time compensation and optimization of the morphology deviation are realized, and finally, a high-precision lens product meeting personalized optical design requirements is manufactured.

The present disclosure is related to blockchain technologies, tokenization and non-fungible token (NFT) technologies, identity verification, account verification, information security (InfoSec), and fraud prevention technologies, and in particular, to technologies for creating NFT identities (IDs) for individuals and / or organizations. An NFT ID service interacts with users to obtain ID information such as ID documents, biographical data, biometric data, and / or any other suitable data. The NFT ID service includes an NFT ID engine that generates an NFT-based form of digitized and / or tokenized ID, using blockchain technology, smart contracts, distributed ledgers, digital wallets, and the ID information. Other embodiments may be described and / or claimed.

A method for enhancing detection of morphed biometric modality data is provided that includes the steps of receiving, by an electronic device, biometric modality data of a person and extracting, using a trained machine learning model operated by the electronic device, high dimensionality feature vectors from the received biometric modality data. Moreover, the method includes the steps of generating a distribution from the high-dimensionality feature vectors, calculating a deviation between the generated distribution and a corresponding record high-dimensionality feature vector distribution of the person, and comparing the calculated deviation against a threshold deviation value. In response to determining the deviation satisfies the threshold deviation value, the method includes the step of determining the received biometric modality data was morphed.

Methods and apparatus for biometric data maintenance, access and distribution across two or more experiential and / or network domains. In one embodiment, a 5G NR-based network architecture is provided which allows ultra-low latency and effectively user-imperceptible biometric data use for e.g., authentication and maintenance of user state across multiple domains via multiple constituent user devices (e.g., UEs). The network architecture includes both (i) a distributed biometric database (BDB) model wherein relevant biometric data for individuals / UEs is intelligently cached in various portions of the distributed database, and (ii) centralized and local BAEs (biometric analytics entities) which manage the aforementioned intelligent caching, as well as network configuration using one or both of 5G NR network “slicing” and CU / DU split options to optimize end-user biometric-related applications such as those providing identification / authentication, AR functions, VR functions or yet others.

The invention relates to the technical field of communication network security, and particularly discloses a distributed communication network security verification method and system, which comprises a two-factor identity authentication module, a dynamic key arrangement and encryption module and a cross-node integrity verification module, and the dynamic key arrangement is respectively connected with the two-factor identity authentication module, the encryption module and the cross-node integrity verification module. Through combination of biological feature anchoring and secure multi-party calculation, on the premise of protecting privacy of original biological data, deep binding of biological features and public keys is realized, and biological uniqueness is given to identity authentication; and dynamic authentication interaction is fused with a timestamp, a biological characteristic entropy value and zero knowledge proof, replay attacks are resisted, 'human-equipment-identity 'consistency is accurately verified, a public key fragment is updated after authentication is passed, an identity trust chain is continuously reinforced, and it is ensured that node identities are true and credible from the source.

A system for adaptive multi-factor authentication using NFC tags in identity management networks, consisting of: an NFC-enabled authentication device configured as a passive label embedded in a smart card, a wearable device, or a physical token, the device including a secure element for storing a cryptographic key pair and a unique device identifier; a terminal device comprising an NFC reader module, a cryptographic coprocessor, a biometric capture interface, and a local control processor configured to initiate a cryptographic challenge-response authentication protocol with the NFC-enabled authentication device upon proximity detection within 10 centimeters; a backend identity management server connected to the end device via a secure communications network, the server comprising a context-aware policy engine, a machine learning-based risk assessment module, and an identity federation interface; wherein, upon receiving a response to a cryptographic challenge signed with the private key embedded in the NFC device, the end device transmits this signed response, biometric data, and context-aware metadata including a timestamp, geolocation of the end device, and device trust level to the backend identity management server; and wherein the backend identity management server evaluates a dynamically generated risk assessment based on real-time behavior analysis, authentication history, and context data and applies an adaptive authentication policy that conditionally permits access;denied or escalated to additional authentication factors.

The invention provides a preschool child emotion intelligent adjusting system based on multi-modal biological recognition, and the system comprises a multi-modal data obtaining module which is used for obtaining the multi-modal biological data of a target child, and carrying out the data preprocessing of the multi-modal biological data, and obtaining a multi-modal data set; the hierarchical feature extraction module is used for performing hierarchical feature extraction on the multi-modal data set to generate a hierarchical vector set; the cross-modal fusion module is used for performing time sequence alignment and dynamic weight fusion on the hierarchical vector set to generate a joint emotion representation vector; the emotion recognition module is used for performing emotion classification processing based on the joint emotion representation vector to generate an emotion recognition result; and the emotion adjustment execution module is used for generating a feedback instruction according to the emotion recognition result, and the feedback instruction is used for indicating the intelligent adjustment device to execute an adjustment strategy matched with the emotion recognition result. The system can effectively capture the hierarchical association of the emotion of the child, and improves the emotion recognition accuracy and the emotion intelligent adjustment pertinence.

A wearable electronic medical device that stores initial baseline biometric data in memory and determines patient-specific thresholds for monitored biometric parameters. Biometric sensors detect changes in these parameters in response to therapeutic treatment or disease progression, and exceeded thresholds activate actions such as patient notifications, changes in treatment, and transmission of data. Trusted receivers receive suggested diagnoses and treatment options determined by an AI-powered web crawler. The treatment includes electrocuetical and pharmaceutical treatment, and the physiological change includes an indication of a change in the cardiovascular condition. The device determines patient-specific thresholds by applying statistical weighting to monitored biometric parameters and determining an acceptable data set.

This disclosure describes embodiments of a closed, permission-only based system that provides a highly secure, identity verification platform that enables users or consumers to protect and manage their own identity related data without relying on a third party source. In general, the system includes a server having a processor, an input interface in communication with the processor, a network interface in communication with the processor, and a processor readable medium in communication with the processor. The processor readable medium stores processor executable instructions. The processor executable instructions, when executed, cause the processor to take the steps of: receiving user data including an image of at least one document; receiving biometric data of the user from a user device of the user; performing validation of said at least one document using said biometric data; and encrypting the user data with an encryption key obtained from the biometric data.

A decentralized digital identity exchange (IDX) is provided. In response to receiving a request for identity verification of a user, the IDX transmits, to a digital wallet associated with the user, a request for current biometric data. The current biometric data is received from the digital wallet and a biometric liveness check is performed. In response to the biometric liveness check succeeding, the IDX generates a verification transaction ID (VTID) and a verifiable credential for the user. The VTID is a unique identifier that comprises a representation of when the identity of the user was verified by the IDX. The verifiable credential and VTID are transmitted to the digital wallet which sends them to a relying party computing system to verify the identity of the user to the relying party computing system.

A ring-type wearable device is provided for sensing biometric data associated with various physiological conditions of the user. In one embodiment, a ring apparatus comprises a ring body including an opening formed therethrough structured to receive a body portion of a user therein when worn by the user; and an electronic computer processor programmed for processing one or more signals detected by the apparatus and associated with one or more biometrics associated with a physiological condition of the user into processed data. A light sensor system connected to the ring body includes multiple light-emitting diodes (LEDs), wherein each LED is associated with a predetermined light wavelength range, a first photodetector configured for light detection in a reflection mode, and a second photodetector configured for light detection in a transmission mode, each for detecting at least a portion of the light originating from the multiple LEDs.

The present disclosure relates generally to implementing biometric authentication, including providing user interfaces for: while the electronic device is in a first state in which a respective function of the electronic device is disabled, detecting one or more activations of the button; and in response to detecting the one or more activations of the button: capturing, with the one or more biometric sensors that are separate from the button, biometric data; if the biometric data satisfies biometric authentication criteria, transitioning the electronic device to a second state in which the respective function of the electronic device is enabled; and if the biometric data does not satisfy the biometric authentication criteria, maintaining the electronic device in the first state and displaying, on the display, an indication that biometric authentication has failed.

A method includes placing a smart ring on a wearer, capturing with a biometric portion, wearer biometric data, determining with a processor, whether the wearer is authorized, in response to the biometric data, determining with the first processor, secure biometric data in response to the biometric data, storing in a memory, wearer secure data, thereafter placing the smart ring proximate to a smart dock, determining with the processor, whether the smart dock and the smart ring are associated, transmitting with a transceiver, the secure data and the secure biometric data, in response to determining that the smart dock is associated with the smart ring, and storing in a secure memory element of the smart dock, the portion of the secure data and the secure biometric data under direction of a processor of the smart dock.

A behavioral analysis platform is a comprehensive system designed to enhance the accuracy of polls and surveys. It utilizes a online survey optimized through payload management and employs machine and deep learning models to analyze behavioral, haptic, or biometric data. The platform captures user behavior, including mouse movements, response times, and other haptic data, using custom APIs. It features a payload manager subsystem for campaign planning and execution, optimizing survey elements for behavioral analytics. The system establishes a behavioral baseline for each respondent, enabling precise analysis of survey responses in terms of conviction, veracity, and sentiment. Real-time adjustments to survey elements and continuous data capture contribute to improved predictive capabilities.

A computer-implemented method of registering a user identifier in a public key infrastructure comprising a trusted device and a server is provided. The method includes the steps: receiving the user identifier as an input to the trusted device; obtaining a hash value of the user identifier; the trusted device obtaining biometric data comprising a facial image of the user; generating a public key and a privacy preserving data structure using the biometric data, encrypting the user identifier using the public key, and storing the encrypted user identifier as metadata in the privacy preserving data structure, wherein a private key for decrypting the encrypted user identifier can be generated from the privacy preserving data structure using subsequently acquired biometric data comprising the facial image of the user; generating a device token corresponding to the trusted device and obtaining a hash value of the device token, the server storing the privacy preserving data structure uniquely indexed by the hash value of the device token while using the hash value of the user identifier as a primary key, and the trusted device storing the device token.

Systems and methods for validating and securing transactions are provided. A registration process can include receiving, via a short-range communication antenna of a mobile device, encrypted data from a contactless card, successfully decrypting the encrypted data to authenticate the contactless card, receiving, via the mobile device, first biometric data, and storing the first biometric data in a biometric profile of a customer account associated with the contactless card. An authorization process can include transmitting a solicitation message to the mobile device responsive to receiving a request to authorize a digital transaction in connection with the customer account, receiving, via the mobile device, second biometric data responsive to the solicitation message, comparing the second biometric data with the biometric profile, authorizing the digital transaction when the second biometric data matches the biometric profile, and denying the digital transaction when the second biometric data fails to match the biometric profile.

Provided is a biometric data monitoring platform using a biometric signal sensing ring. The platform includes a server, wherein the server includes a signal quality classification system including a first signal quality classification component configured to classify signal quality of a first wavelength photoplethysmography (PPG) signal as being good or bad, a biometric data calculation system including an atrial fibrillation determination component configured to determine whether atrial fibrillation has occurred, from the first wavelength PPG signal by using a deep learning model, and a biometric index calculation system including an atrial fibrillation index calculation component configured to calculate an atrial fibrillation index from a first signal quality classification result generated by the first signal quality classification component and an atrial fibrillation determination result generated by the atrial fibrillation determination component.