23925results about "Digital data authentication" patented technology

The present invention provides a facial recognition system using deep learning methodologies while integrating privacy-preserving capabilities. This system employs convolutional neural networks (CNNs) to extract and classify facial features, ensuring high accuracy in recognition tasks. Moreover, the system addresses privacy concerns by incorporating techniques such as facial feature encryption and anonymization, thereby enhancing user privacy and data security. This invention is applicable across various domains, including security, surveillance, access control, and personalized services, where facial recognition is utilized while preserving individual privacy.

A method is provided for improving image classification accuracy in few-shot learning scenarios, where only a limited number of training examples are available. The method combines the use of Gabor filters and convolutional neural networks (CNNs) to extract detailed texture and orientation features from images. These features are then enhanced through global average pooling, aggregated into comprehensive feature vectors, and refined using an attention mechanism that identifies and emphasizes the most relevant features for classification. Masks generated from this attention process selectively enhance critical features, which, after optional re-encoding, are used to train a classifier via a metric learning approach. This method aims to increase feature separability and classification performance, facilitating more accurate classification of new images with minimal training data.

The invention relates to the technical field of firmware protection, in particular to a firmware protection method and system based on a security coprocessor. The method comprises the following steps: acquiring characteristic data of the coprocessor; extracting hardware entropy source data according to the coprocessor feature data; generating a hardware trust root key based on the hardware entropy source data; performing partition processing on the firmware based on the hardware trust root key to obtain firmware partition data; constructing hierarchical verification structure data according to the firmware partition data; implementing firmware starting security verification based on the hierarchical verification structure data to obtain integrity verification data; establishing a secure communication channel between the processors according to the integrity verification data; executing a bidirectional authentication process based on the secure communication channel, and generating session key data; a firmware runtime environment is monitored based on the session key data. According to the method, the hardware entropy source is extracted by measuring the physical characteristics of the coprocessor, and an unforgeable hardware trust root is established, so that the security is improved fundamentally.

Dynamic geofences may be generated and updated based on locations of related assets. For example, locations of a group of related assets, including a primary asset and one or more secondary assets, may be determined. A geofence associated with the primary asset may then be analyzed to identify any geofences of secondary assets that overlap. This process may be repeated for each overlapping geofence to identify additional overlap and expand or move a combined dynamic geofence. Environmental aspects such as time of day, weather conditions, and risk levels may be considered for dynamic geofence adjustments. The combined geofence and asset locations may be displayed on a user interface.

The invention discloses an electronic signature generation and anti-counterfeiting system based on multi-source information fusion, and the system comprises a multi-source information collection module which is used for synchronously obtaining the fingerprint / iris characteristics of a user, the hardware fingerprint of terminal equipment, and the timestamp and geographical location information during operation; the information fusion processing module is used for encrypting and compressing the multi-source information and generating a unique feature vector by adopting a weighted feature fusion algorithm and a block chain encryption anchoring technology; the electronic signature generation module is used for generating a visual signature graph containing a dynamic digital watermark and a multi-layer nested timestamp based on the feature vector, and writing a feature vector hash value into a block chain for evidence storage; and the anti-counterfeiting verification module performs authenticity verification on the signature through a dynamic decryption protocol distributed by a quantum key, and supports reverse feature matching verification based on block chain traceability. According to the invention, the limitation of a traditional single encryption mode is broken through through the cross binding of the multi-mode biological characteristics and the hardware fingerprints in combination with the quantum key and block chain fragmentation technology.

The invention discloses a dynamic collaborative arrangement system and method based on an intelligent agent, and relates to the technical field of artificial intelligence. By integrating core modules of an agent communication protocol, knowledge base management, agent arrangement, security authentication, resource scheduling and the like, not only is a standardized agent cooperation framework and a distributed knowledge sharing mechanism provided, but also dynamic task arrangement and secure and controllable resource scheduling capability among agents are realized. The problem of how to effectively realize standardized communication and dynamic cooperation of agents among enterprises and unified management and shared utilization of knowledge resources in the prior art is solved, and particularly, the problem of how to construct an efficient, safe and extensible agent cooperation network in a multi-enterprise cooperation environment is solved.

Systems and methods for integrating generative artificial intelligence (AI) within Software-as-a-Service (SaaS) platforms to automate data operations, synchronize cross-platform workflows, and enable intent-based interactions. A platform displays table structures of items and characteristics linked to a common objective, provides input interfaces, and enrolls AI agents as credentialed users with read / write privileges. The system prompts agents with column types, structural relations, and role profiles to generate and execute editing instructions that progress workflow objectives, detect missing or inconsistent data, and notify users or request information as needed. Hierarchical access schemes permit multiple agent instances with inherited privileges and resource limits managed through an AI center. Agents can operate as autonomous team members, analyze outputs, and support natural-language explanation sessions. Additional embodiments coordinate inter-service updates, maintain deviation detection tools, and construct tailored products and platform elements. These capabilities improve robust automation, decision support, and operational efficiency in complex SaaS environments.

Systems and methods are described for building artificial intelligence (“AI”) pipelines. A user interface (UI) includes selectable pipeline objects, such as a dataset and an AI model, that a user can position and connect on the screen. This causes execution linking between the selected pipeline objects, with the execution linking being visually displayed in the UI. A management policy can be applied to the pipeline, including user or device requirements for accessing the dataset in the pipeline. Then the UI can present a simulated execution of the AI pipeline, in which a test query is input and the pipeline objects execute in an order displayed in the UI. The pipeline can then be deployed for access at an endpoint.

Providing a customizable generative artificial intelligence (‘AI’) assistant, including: identifying one or more customizations for the generative AI assistant, the generative AI assistant configured to receive information describing a monitored deployment and a natural language input, the generative AI assistant further configured to generate a response to the natural language input; and modifying, based on the one or more customizations, the generative AI assistant.

The invention provides a right and interest exchange verification system, belongs to the technical field of right and interest management systems, and effectively deals with complex right and interest fraud through multi-modal dynamic behavior trust chain construction. The system comprises a multi-modal behavior acquisition module, a real-time acquisition input behavior, equipment and environment characteristics, a federated behavior modeling module, a cross-platform construction dynamic behavior baseline library and trust score output module, a scene risk assessment module, a hierarchical verification strategy supporting module, a dynamic scheduling execution module, and an intelligent resource allocation and auditing module. Data desensitization and feature extraction are realized through lightweight edge calculation; federated learning fuses local and global credit scores, and combines a dynamic attenuation model and scene perception weight adjustment; the multi-modal cross validation is used for coping with different risk levels; the intelligent resource scheduling resists the DDoS attack; the system realizes balance between high-precision fraud identification and user experience through behavior continuity protection, confrontation sample detection and interpretable scoring atlas.

A BIM-based engineering information management system of the present invention relates to the field of constructional engineering informatization management, and comprises a data processing module, a model construction module, a block chain evidence storage module, a verification module, a data fusion module and an authority management module. The data processing module receives original engineering data and generates a structured data signal. And the model construction module generates a BIM model according to the structured data signal. And the block chain evidence storage module encrypts and stores the metadata signal, generates an evidence storage completion signal and feeds back the evidence storage completion signal to the model construction module. And the verification module analyzes the dynamic operation log signal, and generates a risk early warning signal and a repair suggestion signal when abnormality is detected. And the data fusion module generates a fusion data signal, transmits the fusion data signal to the model construction module and triggers BIM model updating. And the authority management module adjusts the user authority according to the risk early warning signal. According to the invention, the problems of data islands, safety risks, low cooperation efficiency and insufficient intelligence in engineering information management can be solved.

The invention discloses a network security verification method and system for a security system, and belongs to the technical field of network security, and the method comprises the steps: obtaining a biological feature recognition request triggered by a user on terminal equipment, synchronously collecting dynamic behavior track data, and generating a behavior feature code; inputting physiological feature data and behavior feature codes in the biological feature recognition request into a feature verification model, when an output biological behavior correlation index is lower than a first preset threshold value, triggering a dynamic verification strategy adjustment instruction, generating a multi-dimensional verification superposition strategy, and executing at least two verification operations in the multi-dimensional verification superposition strategy, the verification result is input into the distributed time synchronization node to generate an encryption token; and when the synchronous matching degree of the encryption token among different nodes exceeds a second preset threshold value, outputting a security verification passing instruction. According to the method, multi-modal feature fusion, dynamic hierarchical verification and time-space encryption technologies are adopted, replay attacks are prevented, an adaptive defense system is constructed, and reliable authentication of a high-security network scene is ensured.

To provide a vehicle control system that can suppress a vehicle from operating even after the vehicle is brought into an operable state by an activity of an improper user.SOLUTION: Vehicle control systems (1, 1a and 1b) comprise: start-notification transmitting parts (relay servers 71 and 71a, and an operation support ECU 21a) which transmit operation start-notifications to one or a plurality of registered terminals (portable terminals 6, 6a, 6b, and 6c) associated with vehicles (2, 2a, and 2b) in accordance with operation of starting the vehicles; and operation control parts (driving support ECU 21, 21a, and 21b) which when operation control request operation is performed to the registered terminals in response to the operation-start notifications, switch the vehicles between an operation suppression state and an operation possible state.SELECTED DRAWING: Figure 6

A behavioral authorship verification system captures and analyzes multi-modal behavioral patterns during content creation to authenticate human authorship. The system comprises a processor executing behavioral analysis modules that generate comprehensive behavioral fingerprints distinguishing genuine human authors from AI-generated content and impostor authorship. A sentence progression mapping module detects sentence boundaries and captures intermediate composition states including additions, deletions, and modifications. A multi-modal input analysis module monitors keystroke dynamics including flight time and dwell time while detecting paste events and input method transitions. A behavioral pattern recognition engine generates user-specific baselines from historical sessions and computes deviation scores using statistical distance metrics. An anomaly correlation module aggregates behavioral deviation signals using weighted fusion algorithms to detect sophisticated mimicry attempts. An authorship scoring engine synthesizes outputs into unified confidence scores while maintaining temporal authorship chains. The system enables real-time authorship verification during content creation rather than post-hoc analysis.

Systems, methods, and computer program products are disclosed for selectively employing a processing mode based on a continuous gesture. Selectively employing a processing mode may include detecting an existence of a mode-selection gesture by an individual. Upon detecting the existence of the mode-selection gesture, a first mode for processing facial micromovements of the individual may be continuously implemented while continuously detecting the mode-selection gesture. Following the continuous detection of the mode-selection gesture, a cessation of the mode-selection gesture may be detected. In response, implementation of the first mode may cease, and implementation of a second mode different from the first mode may be initiated for processing facial micromovements of the individual.

The invention belongs to the technical field of computer data protection, and particularly relates to a computer data hierarchical protection method and a dynamic protection system. According to the method, the to-be-protected data is graded and scored, dynamic adjustment of the data protection grade is realized in combination with the dynamic risk of the computer network environment, and more detailed data grading is performed in combination with the semantic risk value by identifying sensitive information in the to-be-protected data, so that the pertinence and effectiveness of data protection are ensured, and the data protection efficiency is improved. Meanwhile, multiple risk parameters of the computer network environment are comprehensively considered, the security state of the network environment is reflected in real time through calculation of the dynamic risk score value, the data protection grade is intelligently adjusted according to the grading score and the dynamic risk score value, and dynamic optimization of the data protection strategy is achieved; and through fusion of historical behavior records and current session contexts of operators, fine management of access permissions is realized, and the security of data access is further enhanced.

Systems, methods, and computer program products are disclosed for generating a common record based on differing source inputs. Generating a common record based on differing source inputs may include receiving via at least one sensor first non-audible signals indicative of verbalization of an individual; interpreting first words of the individual at least in part using the first non-audible signals received from the at least one sensor; receiving second signals generated by a source other than the individual; performing speech recognition on the second signals to interpret second words from the source; and using the first words and the second words to generate a record.

The invention relates to the technical field of big data, in particular to a cloud computing-based tumor early screening data sharing platform construction method and system. The sharing platform construction method comprises the following steps: carrying out association modeling on multi-dimensional early screening data by adopting a knowledge graph technology; encrypting the sensitive field of the metadata index database, and synchronously generating an irreversible anonymous identifier to replace the original identifier; partitioning and arranging the metadata index database in a distributed storage system corresponding to a cloud platform according to tumor types, and performing cross-region redundant backup by adopting an erasure code technology; and constructing an access control smart contract based on a block chain technology, verifying the qualification of a requester through a digital identity authentication module, and after verifying the validity of a digital certificate of the requester, dynamically decrypting and transmitting a data copy conforming to an authority level. Through organic fusion of the knowledge graph, the encryption technology, distributed storage and the block chain, a safe, efficient and reliable tumor early screening data sharing platform is constructed.

The invention discloses a dynamic authority management system and method based on multi-source salary data integration, and relates to the technical field of salary data management, and the method comprises the following steps: collecting role names, authority boundaries and operation granularity information from a plurality of business systems, and generating structured role semantic ontology entries based on a field-level semantic annotation mode; and disassembling the to-be-mapped role according to the authority dimension, calculating a semantic similarity index between the to-be-mapped role and the standard role based on the role semantic ontology library, and outputting a role consistency scoring matrix. According to the method, the authority difference is identified through the role semantic ontology and the similarity score, the minimum authorization judgment is realized in combination with the rule engine and reinforcement learning, the audit traceability and anomaly detection are guaranteed by using the block chain and the dynamic graph, and finally a strategy self-evolution closed loop is constructed. And the problems of permission mismatching and data leakage caused by role semantic inconsistency are effectively solved.

The invention provides an augmented reality cooperation system for a cloud desktop, and the system comprises a cloud service module which generates a virtual desktop image, and carries out the resource monitoring and data storage; the AR equipment is used for collecting data and interacting with virtual reality; the collaborative rendering module is used for fusing AR rendering and virtual reality; the interaction module is used for a multi-modal interaction mode and personalized recommendation; the intelligent scheduling module is used for dynamic resource allocation, resource prediction and optimal management; the network optimization module is used for designing a layered edge architecture and introducing a QUIC protocol to carry out optimized transmission of data streams; the security module is used for carrying out encryption transmission and verifying the identity and access of the user; and the compatible module is used for defining standardized interfaces and protocols and realizing multi-platform support. Functions and resources can be deeply fused, the problems of network dependence, interaction precision, resource allocation and the like are solved, optimal AR presentation and experience effects are provided, and various application scenes are supported.

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 invention discloses a fine-grained access control method and system based on risk identification, and belongs to the technical field of information security. According to the method, user subject attributes, behavior attributes and system environment attribute information are collected in real time, a standardized decision matrix is constructed, an interval type-2 fuzzy set (IT2FS) is used for conducting fuzzy modeling on the attributes, and an upper membership matrix and a lower membership matrix are generated. And calculating the dynamic weight of the attribute index in combination with a CRITIC method, introducing a time decay factor to dynamically correct a risk score through an improved TOPSIS method, calculating the Euclidean distance between an access request and a positive / negative ideal solution, and generating a normalized risk closeness degree. And based on the risk score and a preset threshold value, dynamically matching a hierarchical permission strategy, and adopting a static rule and a priority coverage mechanism to eliminate permission conflicts. According to the method, multi-dimensional risk assessment and dynamic weight adjustment are fused, the problems of insufficient real-time performance, subjective weight dependence and weak uncertainty processing capability in a traditional method are solved, the accuracy and security of access control are remarkably improved, and the method is suitable for scenes with high security requirements such as cloud computing and finance.

The invention relates to the technical field of data analysis, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a decision generation method based on multi-dimensional data verification, which comprises the following steps: receiving an authentication request and completing operation authority granting, obtaining a target data set, and performing multi-dimensional verification on the target data set based on an analysis strategy set, generating a first verification result, performing multi-source consistency verification through an authenticity verification service interface, generating a second verification result, generating a candidate decision scheme set based on data features of the first verification result and the second verification result, and generating a decision file containing an analysis conclusion according to the candidate decision scheme set. And feeding back the generation state of the decision file. According to the method, a scheme generation and feedback mechanism driven by the data verification result is constructed, so that joint verification of compliance and authenticity of the target data set is realized, and the interpretability of the result and the transparency of data processing are guaranteed while the decision-making efficiency is improved.

A generative artificial intelligence (AI) system includes a generative AI model configured to generate outputs based on a training data set. The AI system additionally includes a secure data vault system. The secure data vault system additionally includes a sandbox system storing the generative AI model and operatively coupled to the generative AI model to send inputs to generate the outputs from the generative AI model, wherein the sandbox system comprises an execution environment configured to restrict execution of the generative AI model to a predefined memory address range. The secure data vault system further includes a secure network service communicatively coupled to the sandbox system and configured to authenticate a connection to an external system and to download from the external system an update package for the generative AI model when the connection is authenticated.

Systems and methods are described for transmitting broadcasts by Peripherals, receiving the broadcasts by Centrals, and communicating with a Backend by Centrals. Specifically, a Peripheral may generate and transmit an encrypted broadcast packet to a Central, the Central may transmit the encrypted observation information to the Backend, which may decrypt the broadcast packet. Additionally, a Central may transmit a request for authorization to connect to a Peripheral to the Backend. If authorized by the Backend, the Central may connect to the Peripheral. Further, a Central may receive a plurality of broadcasts over a period of time. The Central may store information about the broadcasts and, at the conclusion of the period of time, transmit the information about the broadcasts and the last-received broadcast to the Backend.

The present disclosure relates to configured artificial intelligence methods and systems and related transportation systems and methods, including software-defined vehicles, for transportation systems using sensor and other data, and the integration of a transportation system with an AI convergence system of systems, providing a multi-layered system for intelligent automation and data-driven decision making across operational aspects of a transportation system.

Systems, methods, and computer program products are disclosed for establishing nonvocalized communications. Establishing nonvocalized communications may include detecting a directional gesture made by a wearer of a first wearable device configured to determine facial skin micromovements of the wearer, wherein the directional gesture identifies a second device in proximity to the first wearable device. Based on the directional gesture, a wireless communication channel for enabling a nonvocalized communication between the first wearable device and the second device is selected. Thereafter, specific facial skin micromovements of the wearer of the first wearable device are determined. The specific facial skin micromovements indicate words to be communicated in an absence of perceptible vocalization by the wearer of the first wearable device. Then, the words are transmitted via the wireless communication channel from the first wearable device to the second device for presentation via the second device.

The invention belongs to the technical field of information data security, and particularly relates to an equipment attribute verification method based on a block chain and zero-knowledge proof. The invention relates to four main roles: a data collector, a block chain platform, a data consumer as a certifier, and an authorization supervisor as a verifier. Through combination of a block chain technology and zero-knowledge proof, verification of inherent attributes and dynamic attributes of decentralized equipment is carried out, and data integrity and user privacy are ensured at the same time; a solution is provided for managing access permissions of equipment across different regions, wherein the access permissions are determined by factors such as equipment identities, user roles and geographic positions. The system reduces the burden of the block chain by using decentralized storage, realizes safe access verification through zero-knowledge proof, and does not expose sensitive data at the same time; according to the invention, more flexible and accurate equipment authentication can be realized, and the method is especially suitable for complex equipment management requirements in medical scenes.

The invention provides a safety monitoring method and system for a financial information service platform. Wherein a collaborative encryption transmission channel between a budgeting unit and an auditing department is constructed, a joint key is generated based on a multi-party computing protocol, and the ciphertext operation authority of a sensitive field is dynamically configured; performing ciphertext variance calculation and regression analysis on the encrypted budget execution record through the security operation node, generating a verifiable statistical result, binding the authority, and synchronously updating the sensitive field access frequency; a hierarchical security threat baseline is generated in combination with permission, frequency and historical query records, and cross-project high-frequency query and data operation deviation are associated; and when the query deviates from the baseline, calculating the risk confidence coefficient according to the deviation, triggering multi-party verification path adjustment and collaborative alarm, and dynamically limiting the ciphertext permission of the abnormal query. According to the technical scheme provided by the invention, cross-department data security sharing and dynamic risk collaborative prevention and control are realized.