1441 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.

The present disclosure provides a method for secure verification of identities. The method includes obtaining personal identifying information from an individual using a remote device and transmitting the information to an application service. The application service accesses multiple disparate data sources via an API, including public entity data sources, third party data sources, and services sources. The API normalizes data received from the disparate data sources. The personal identifying information is verified against the normalized data. Biometric identifying information is obtained from the individual using the remote device and transmitted to the application service. The biometric identifying information is compared with normalized biometric data from the disparate data sources. Based on the comparison, a determination is made whether to issue a digital identification credential to the individual. An authentication result is transmitted to the remote device.

A set of distance measurable encrypted feature vectors can be derived from any biometric data and / or physical or logical user behavioral data, and then using an associated deep neural network (“DNN”) on the output (i.e., biometric feature vector and / or behavioral feature vectors, etc.) an authentication system can determine matches or execute searches on encrypted data. Behavioral or biometric encrypted feature vectors can be stored and / or used in conjunction with respective classifications, or in subsequent comparisons without fear of compromising the original data. In various embodiments, the original behavioral and / or biometric data is discarded responsive to generating the encrypted vectors. In another embodiment, distance measurable or homomorphic encryption enables computations and comparisons on cypher-text without decryption of the encrypted feature vectors. Security of such privacy enabled embeddings can be increased by implementing an assurance factor (e.g., liveness) to establish a submitted credential has not been spoofed or faked.

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.

A method for enhancing detection of fraudulent data is provided that includes the step of analyzing, by an electronic device, voice biometric data captured while the user was speaking to determine whether the captured voice biometric data exhibits anomalies associated with fraudulent voice audio data. Moreover, the method includes the steps of analyzing circumstances under which the voice biometric data was captured, analyzing mannerisms of the user while the voice biometric data was captured, and calculating a risk score based on at least the results of the analyses. Furthermore, the method includes the steps of comparing the risk score against a threshold value, and in response to determining the risk score fails to satisfy the threshold value generating an alert having a risk level corresponding to the risk score.

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 for AI-based analysis of student behavior, consisting of: a variety of data collection devices, including cameras, microphones and wearable sensors; a central processing unit (CPU) that is communicatively connected to the data acquisition devices; and a behavioral analysis engine, wherein: (a) the cameras are configured to capture visual data indicating student behavior, including facial expressions, body language and eye movements, with the captured visual data being processed using computer vision techniques to detect certain emotional and engagement-related indicators such as stress, boredom, attention or excitement; (b) the microphones are configured to capture audio data, including speech patterns, tone of voice, volume and level of participation, the captured audio data being processed using natural language processing (NLP) techniques to assess the mood, engagement and verbal participation of students in classroom activities; (c) the wearable sensors are configured to collect biometric data, including heart rate, skin temperature and movement, with the biometric data being analyzed to detect physiological signs of emotional stress, fatigue or engagement; (d) The behavioral analysis engine is configured to process the captured visual, auditory, and biometric data in real time to create a behavioral profile of each student. It uses machine learning models to correlate certain patterns with academic performance, emotional well-being, and social engagement. (e) the system is also configured to create predictive models based on historical data to identify pupils at risk of declining performance, social isolation or emotional distress, and to send alerts to teachers, counselors or the administration to enable timely intervention to address the identified problems.

Disclosed are example methods, systems, and devices that allow for secure digital authorization via generated datasets. The techniques include receiving a first dataset of a first user and a second dataset of a second user and generating a first set of identity elements and a second set of identity elements based on the first dataset and the second dataset, respectively. A linkage definition can be generated based on the first and second datasets, which can be associated with a set of activation elements. The techniques include determining that a set of inputs satisfy one or more of the set of activation elements and, in response, generating a set of security access tokens based on the linkage condition. The security access tokens can be transmitted to a computing device upon analyzing and verifying biometric data received from that computing device.

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.

A processing system deployed in a carrier transport vehicle may establish a wireless communication session with a mobile device of a user, assign a zone of the carrier transport vehicle to the user, the zone including a plurality of network-connected devices, obtain a user profile from the mobile device of the user, determine at least one biometric sensor accessible via the mobile device of the user, obtain biometric data of the user from the at least one biometric sensor accessible via the mobile device of the user, determine a condition of the user based upon the biometric data, identify at least one adjustment to at least one of the plurality of network-connected devices in response to the condition of the user that is determined and the user profile, and apply the at least one adjustment to the at least one of the plurality of network-connected devices.

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.

A method for a control system includes receiving in a biometric capture portion of a wearable device worn by a wearer, wearer biometric data associated with the wearer, storing in a memory of the wearable device authentic biometric data associated with an authorized user and a private key associated with the wearable device, receiving in a first short-range transceiver of the wearable device payload data, determining in a first processor of the wearable device if the wearer biometric data is authentic in response to the authentic biometric data associated with of the authorized user, encrypting in the first processor the payload data to form encrypted data in response the private key and in response to determining that the wearer biometric data is authentic, and outputting with the first short-range transceiver the encrypted data in response to determining that the wearer biometric data is authentic.

The system (1000) and method are based on the generation of at least one individual biometric identifier – IBI - from at least user representative synthetic data {Ns} (S70), said user representative synthetic data being generated from neural data {N} of said user (10) received by a pre- trained generative model. Said at least one IBI enables to authenticate said user (10) when compared to at least one user's signature stored in a memory (40). Said at least one IBI can replace both identifier and password to authenticate and login said user (10) without containing any personal biometric data, guaranteeing the anonymity of the login data that can be exchanged remotely.

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.

A system and method for passwordless authentication for accessing a remote system is disclosed. The system includes an authentication server, a database, and a user computing device. The user computing device is configured to send a request to the authentication server. The authentication server is configured to generate, a lattice matrix, store the lattice matrix in the database, and return a lattice generator matrix (LGM) to the user computing device. The user computing device is further configured to compute a bioquantum of biometric data of a user based on the LGM using a post-quantum fuzzy commitment scheme (PQFC) and send the bioquantum to the authentication server for storage in the database.

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.

Sensor data may be captured by at least one sensor in communication with at least one processor. The at least one processor may extract biometric data from the sensor data and compare the biometric data with stored biometric data for a first user stored in a memory in communication with the at least one processor. The at least one processor may determine that the biometric data matches the stored biometric data based on the comparing. The at least one processor may execute a transaction between the first user and a second user, the transaction comprising an exchange of digital currency between the users. The at least one processor may create a block in a distributed blockchain, the block comprising data memorializing the at least one transaction including information describing the exchange of the digital currency and at least one of the biometric data and the stored biometric data.

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.

Methods and systems for secure media processing may be used to execute and certify a digital media asset by verifying that the digital media asset is authentic and has not been altered since capture. In some cases, these secure media processing techniques may be used in the mobile certification and execution application and a corresponding server system. The mobile application and the corresponding server system may automatically generate finalized documents upon receiving certified digital media and the corresponding metadata from the users. The digital media and other information from the users may be received while the user is in communication with other users. A biometric and artificial intelligent feature recognition system may be utilized to receive biometric data and verify identity. Data transferred to a secure server are accessible by various parties involved in the certification and execution process to provide transparency.