34 results about "Data disclosure" patented technology

Aspects of the subject disclosure may include, for example, receiving first data from a communication device over a mobile network, and determining that the first data is associated with a first user profile associated with the communication device. Further embodiments can include determining that the first user profile is associated with a first group of mobile network resources, and transmitting the first data across the mobile network utilizing the first group of mobile network resources. Other embodiments are disclosed.

Example methods disclosed herein include accessing public housing data for a set of public housing, the public housing data including return path data and small group meter data. Example methods disclosed also include accessing public housing data for a set of public housing, the public housing data including first return path data and respective small group meter data associated with individual public housing of the public housing; grouping the public housing data into viewing segments; classifying the viewing segments based on whether the return path data in individual ones of the viewing segments has matching small group meter data to determine labeled viewing segments; generating features from the labeled viewing segments; training a machine learning algorithm based on the features; and applying second return path data to the trained machine learning algorithm to determine whether a media device associated with the second return path data is on or off.

The invention provides a data protection method and device, a data access method and device, equipment, a medium and a product. The data protection method comprises the steps that first data extracted from to-be-protected target data is publically published to a block chain; encrypting second data extracted from the target data, and storing the encrypted second data; generating a key question and a key answer corresponding to the key question according to the content, which is not disclosed in the first data, in the target data; and storing the key question and the key answer in a smart contract of the block chain, so that the smart contract sends the key question to a second terminal when the second terminal requests the block chain to access the first data, and in response to receiving answer information matching the key answer from the second terminal, transmitting a key for decrypting the encrypted second data to the second terminal.

An artificial intelligence (AI)-based system for detecting malware in endpoint devices using a multi-source data fusion and method thereof are disclosed. The AI-based system collects at least one of: endpoint visibility data, publicly available information, and sandbox analysis data using the multi-source data fusion. By using the collected data, the AI-based system generates one or more numerical embeddings for at least one of: one or more files and one or more applications of each endpoint device using one or more AI models. The AI-based system is configured with the one or more AI models to generate one or more dynamic directed graphs based on the generated one or more numerical embeddings to compute a maliciousness risk score. The maliciousness risk score of at least one of the: one or more files and one or more applications is used for detecting the malware in the one or more endpoint devices.

The invention discloses a block chain-based verification method and electronic equipment, and the method comprises the steps: carrying out the analysis of a transaction request, and obtaining identity certificate data carried by the transaction request; wherein the identity certificate data is generated based on the relationship between the transaction account and the account blacklist and the version information of the account blacklist; calculating the identity data according to a preset function to obtain to-be-verified data; generating first verification data according to a public key corresponding to the account blacklist and the to-be-verified data, and generating second verification data according to the public generator and the to-be-verified data; the public generator is a preset public parameter; and verifying the transaction request according to the identity proof data, the first verification value and the second verification value. According to the technical scheme, the volume of the verification data is compressed, the data transmission amount and the calculation amount of the block chain node in the verification process are reduced, and the verification speed of the transaction request can be remarkably improved.

Aspects of the subject disclosure may include, for example, providing a standard request for usage of one or more frequencies to an automated frequency coordination (AFC) system, where the request includes a location of a low power indoor transmitter that is a subject of the request. The aspects may include receiving data identifying at least one frequency channel and a power limit for the at least one frequency channel from the AFC system, where the at least one frequency channel and the power limit are determined by the AFC system to reduce interference with existing standard power access points based on the location of the low power indoor transmitter. The aspect may include providing the data identifying the at least one frequency channel and the power limit to the low power indoor transmitter. Other embodiments are disclosed.

Techniques for managing data stored within a database, such as a decentralized database are provided. Some techniques involve managing some data within a lower-trust database and some other data within a higher-trust database. A higher-trust database may be a decentralize database including a blockchain. A lower-trust database may store references to data within the blockchain, and optionally other data in association with those references. Disclosed techniques include WHERE clause query handling in databases with reference values, replacement of distinct data in a relational database with a distinct reference to that data, number line storing for secure indexing, APIs for databases, and consensus operations for private blockchain networks.

The utility model discloses a quantum key distribution system terminal based on zero trust. The quantum key distribution system terminal comprises an Alice sending end, a Bob receiving end and a zero trust server, the zero-trust server comprises an identity authentication server and a key management server; the utility model discloses a quantum key distribution system terminal based on zero trust, which respectively performs identity authentication on an Alice sending end and a Bob receiving end through an identity authentication server, effectively prevents malicious operations such as malicious impersonation, resource access and data leakage of a user, realizes continuous verification and monitoring on the user, equipment and a system, and improves the user experience. The current complex and changeable network environment can be met, and the safety and reliability of communication between nodes in the QKD network are improved.

The present application relates to the field of Internet of Things security and computing scheduling, and particularly relates to a kind of end edge cloud multistage multi-domain access control method, which method includes: first according to service level requirement and compliance clause generates intention constraint description and establishes session root and one-time session token;Each layer carries remote proof and execution commitment and submits bid in parallel, and control plane verifies to form a bid package set;Under the constraint, joint arrangement solution is determined, stage is settled and cross-domain data path is determined, and minimum data disclosure rule and minimum feasible plan are generated, and stage token is issued;Each stage executes according to token and generates execution proof, and control plane verifies and enters account after verification, and switches between backup plan and current plan according to verification and operation monitoring, and completes verifiable and traceable operation closed loop.

The application discloses a supplier green dynamic evaluation method and system based on carbon footprint data driving, and relates to the technical field of environmental protection and low carbon, wherein the method comprises the following steps: obtaining effective data of a supplier and green certification data of an industry to which the supplier belongs; performing carbon footprint accounting based on the effective data and the green certification data, obtaining carbon performance results of the supplier, and updating green evaluation information of the supplier according to the carbon performance results; listening to a target event message, refreshing the green evaluation information based on the target event message; and calculating a comprehensive green score of the supplier based on the target event message and the effective data. The scheme can improve the data updating timeliness and industry adaptation accuracy of the supplier green evaluation, timely respond to carbon data disclosure policy requirements, and thus help enterprises improve the green risk management level of a supply chain.

The disclosed system may include a non-transitory memory and one or more hardware processors configured to execute instructions from the non-transitory memory to perform operations including determining online data and offline data from a mobile application, wherein the online data is determined based on the mobile application being online and the offline data is determined based on the mobile application being offline, determining travel distance data from a remote device associated with the vehicle, aggregating at least a portion of the online data, at least a portion of the offline data, and at least a portion of the travel distance data, generating data associated with the aggregation of the portion of the online data, the portion of the offline data, and the portion of the travel distance data, and causing the mobile application to display the generated data. Other methods, systems, and computer-readable media are disclosed.

This invention relates to the field of artificial intelligence technology in mining, and particularly to a method, apparatus, and equipment for fine-tuning and distillation of a coal mine underground model. The method includes: initial supervised fine-tuning of a teacher model and a target model using a precisely labeled dataset; performing multi-channel parallel inference on an unlabeled dataset using the initial teacher model and the target model, and constructing a high-quality distillation dataset after consistency verification and quality screening; fusing precisely labeled data, publicly available general data, and distillation data to form a comprehensive training set, and performing secondary supervised fine-tuning of the target model using multi-loss fusion; iteratively updating and quality-evaluating the distillation dataset based on the optimized target model, and performing enhanced fine-tuning using a thought chain inference template to obtain a final model adapted to edge devices. This invention effectively utilizes multi-source underground data and reduces labeling costs, significantly improving the model's adaptability, inference efficiency, and robustness in anomaly detection in complex underground environments, achieving a synergistic optimization of high accuracy and low resource consumption.

In various examples, contextual data may be generated using structured and unstructured data for conversational AI systems and applications. Systems and methods are disclosed that use structured data (converted to unstructured form) and unstructured data, such as from a knowledge database(s), to generate contextual data. For instance, the contextual data may represent text (e.g., narratives), where a first portion of the text is generated using the structured data and a second portion of the text is generated using the unstructured data. The systems and methods may then use a neural network(s), such as a neural network(s) associated with a dialogue manager, to process input data representing a request (e.g., a query) and the contextual data in order to generate a response to the request. For instance, if the request includes a query for information associated with a topic, the neural network(s) may generate a response that includes the requested information.

The invention belongs to the field of data encryption, and relates to a multi-data source technology layout strategy generation method, which comprises the following contents: constructing a training database, and taking the training database as a data source, the training database comprising public data and private data, the public data comprising patent data and paper data, and the private data comprising private technology experiment data; private data are encrypted through a data preprocessing module, encrypted training data are obtained, and in the training process, encrypted language conversion is carried out on the encrypted training data through an encryption large model; constructing an encrypted language interpreter, and converting the encrypted training data into a common language through the encrypted language interpreter; and carrying out technical layout strategy generation model training on the encrypted large model through public data and a common language converted and output by the encrypted language interpreter, and obtaining a technical layout strategy generation model through training.

Aspects of the subject disclosure may include, for example, a drone service retrieving network state information describing a network state of at least a portion of a communication network, determining an impact of the network state on operation of an unmanned aerial vehicle (UAV), selecting a carrier frequency to be used for communication by the UAV, and providing the data describing the carrier frequency to the UAV and / or to communication network nodes. Other embodiments are disclosed.

The application relates to the technical field of battery passport, and discloses a battery data cross-border transmission method, device, equipment and readable storage medium. The method comprises the following steps: obtaining battery data of a target battery, and generating a full-amount supply chain knowledge graph corresponding to the target battery based on the battery data; performing data review on the basis of preset cross-border transmission regulations and the full-amount supply chain knowledge graph by a preset game intelligent agent, determining a legal quasi-outbound data set and an unexportable confidential data task list; performing zero-knowledge proof processing on the unexportable confidential data task list, generating a zero-knowledge proof string, and encapsulating the legal quasi-outbound data set and the zero-knowledge proof string to generate a battery data compliance digital certificate; and sending the battery data compliance digital certificate to an overseas node. When the battery data is cross-border transmitted, the overseas data disclosure requirement can be met, and core confidential data leakage can be avoided.

This network node: receives, from a first node, a message that requests terminal model training data and that includes an application server identifier and a terminal group identifier; derives a terminal identifier that belongs to a terminal group which is indicated by the terminal group identifier; receives, from a second node and for each terminal identifier, a message that includes information indicating whether or not a user consent related to data disclosure to an application server which is indicated by the application server identifier is given; transmits, to a third node, a message that requests terminal model training data and that includes a list of terminal identifiers to which the user consent is given; receives, from the third node, a message that includes terminal model training data corresponding to the list of the terminal identifiers to which the user consent is given; and transmits, to the first node, a message that includes the terminal model training data corresponding to the list of the terminal identifiers to which the user consent is given.

Various aspects of the present disclosure relate to generating data and analytics based at least in part on both internal wireless communications system data and on external data. The internal wireless communications system data is, for example, internal data of the wireless communications system that describes operation of the wireless communications system. The external data is, for example, data external to the wireless communications system that the apparatus has access to (e.g., data that the wireless communications system accesses with authentication from an owner of the external data, publicly available data, and so forth). An entity of the wireless communications system receives requests from a 3rd party consumer, generates the requested data and analytics, and returns the requested data to the 3rd party consumer.

The invention discloses an enterprise credit granting processing method, device and equipment, a medium and a product, and relates to the field of financial science and technology. The method comprises the following steps: acquiring public financial data and public property data of a target enterprise and industry technical information of a target industry; determining at least one enterprise technology point of the target enterprise according to the public known production data and the industry technology information; determining the attention weight of each enterprise technology point relative to each technology hotspot in the industry technology information based on the public known production data and each enterprise technology point; and determining a credit granting result of the target enterprise according to the public financial data, the technical point of each enterprise and the attention weight. According to the technical scheme of the embodiment of the invention, the multi-dimensional heterogeneous data processing efficiency and the credit extension accuracy in the credit extension process can be effectively improved, and the method has good universality and adaptability.

In a data cooperation system in which information cooperates in a first system, a second system and a third system, the first system provides an already operating service and collects and publicizes behavior data as information for providing the service, the second system acquires the behavior data, generates a verification result applying the behavior data to a new technology as verification data, and publicizes the verification data, and the third system receives the behavior data and the verification data, supports decision of the determination result data, and publicizes the decided determination result data.

Existing privacy-preserving techniques suffer from inherent drawbacks to retain characteristics of observed, and original industrial time series data for utility in the downstream tasks such as process modelling, control, optimization and etc. The embodiments herein provide a method and system for privacy preserving generative mechanism for data-disclosure of the industrial multivariate mixed-variable time series data. The system fuses an industrial time series data with a random gaussian noise to preserve the privacy of the industrial time series data and trades-off the privacy with the utility of synthetic-private data. Further, the system presents the privacy-preserving synthetic industrial data generative mechanism for data disclosure with minimal risk of AI technique and strong privacy guarantees. Embedding privacy by design into the generative mechanism approaches present an alternate paradigm of learning in contrast to the reduced-order modeling and numerical solutions of the industrial time-series data based on the principles in continuum mechanics for data disclosure with privacy.

The utility model provides an isolated transmission terminal based on industrial network interconnection, including terminal shell, the transmission mechanism is equipped with in terminal shell inner bottom wall, and terminal shell inner bottom wall one side is equipped with moving mechanism, and terminal shell inner bottom wall other side is equipped with limit mechanism, and fixed mounting of fixed plate has in transmission terminal shell one end, the utility model discloses through fingerprint sensor carries out the right verification, only the fingerprint of authorized personnel is identified, motor will start, drives screw rod rotation, and then drives the mobile block and the moving plate to move down, makes the terminal machine to show in the user's face, and the user operation is convenient, has guaranteed that the terminal machine will not be contacted at random under the unauthorization condition, effectively prevents data disclosure and illegal operation, and the user can carry out data transmission operation fast, conveniently after through fingerprint verification, realizes efficient data exchange through data transmission mouth, has improved work efficiency greatly.

The invention relates to the technical field of block chains and information security, and particularly discloses an electronic license stream storage method fused with a block chain smart contract, which comprises the following steps: firstly, converting a natural language service strategy into a multi-dimensional strategy matrix executable on a chain, and introducing a scene attribute certificate endorsed by an authority; and the strong binding between the identity and the environment context is realized. In the circulation process, the intelligent contract serves as a strategy decision point, adaptive calculation is carried out on a multi-dimensional attribute vector of a requester through a strategy tensor projection and continuous environment factor correction algorithm, and a permission field mask containing refined permission is generated in real time. Finally, based on the mask, a temporary authorization token with timeliness is generated, and through an audit log closed loop which cannot be tampered on a chain, the traceability of the whole process of minimization disclosure and circulation of the electronic license data in a complex service scene is ensured.

Exemplary embodiments may employ artificial intelligence models to identify outbound emails (e.g., those directed to recipients that are outside an organization, a business unit or other partition of an organization) that are at risk of containing IDDs. The identified emails may be automatically blocked and / or may be forwarded to a reviewer for further scrutiny and / or remediation. The reviewer may review the emails and determine whether the emails should be blocked from being sent and / or whether the email should be remediated. The identified emails may be returned to their senders or associated business unit or organization, and the senders or remediating parties may modify the emails and attempt to send out the modified emails.

To provide a message disclosure system for giving a sense of security and satisfaction to a person who receives a message by disclosing the message from an insurance contractor or an insured person to an insurance money receiver when a prescribed event occurs in the insurance contractor or the insured person.SOLUTION: In a message disclosure system 1 consisting of one or a plurality of servers for storing, managing and disclosing the status information data and message data of the first customer, the server includes at least a storage part, an arithmetic part and a disclosure processing part, and the arithmetic part registers the event information acquired by an event acquisition means in a customer information database by a customer status storage / management means. When the event information is a fixed value, a disclosure propriety determination means determines the propriety of the disclosure of the message data to the second customer, and when it is determined that the disclosure is possible, instructs a disclosure processing part to perform disclosure processing of the message data to the second customer.SELECTED DRAWING: Figure 1

The invention provides a cloud side-end collaborative building energy-saving and carbon-reducing transformation scheme generation design system and method. The system comprises an information acquisition module, an SQL database module, a user query module and a design decision module. According to the system and the method, multi-source heterogeneous sensing data can be effectively integrated, and a unified data processing mechanism can be established; meanwhile, an online data disclosure and collaborative optimization platform for collaborating users, architects and construction parties can be established, so that the users can effectively participate in a reconstruction scheme design decision; and the dispatching management of enclosure structure components and the building carbon reduction design technology can be effectively linked.

In various examples, contextual data may be generated using structured and unstructured data for conversational AI systems and applications. Systems and methods are disclosed that use structured data (converted to unstructured form) and unstructured data, such as from a knowledge database(s), to generate contextual data. For instance, the contextual data may represent text (e.g., narratives), where a first portion of the text is generated using the structured data and a second portion of the text is generated using the unstructured data. The systems and methods may then use a neural network(s), such as a neural network(s) associated with a dialogue manager, to process input data representing a request (e.g., a query) and the contextual data in order to generate a response to the request. For instance, if the request includes a query for information associated with a topic, the neural network(s) may generate a response that includes the requested information.

Techniques used by an observability system for facilitating near real-time analytics using structures representing or summarizing data distributions, such as histograms. An observability system receives a set of datapoints in which each received datapoint includes data for a structure representing a data distribution. For example, each of the datapoints may include data for a histogram including at least two dimensions. A processing pipeline is disclosed for processing the received data and making the results of the processing available to a user in near real-time. The processing includes identifying, from the datapoints received by the observability system, a subset of datapoints that fall within a time window, generating aggregate data based upon data in the identified subset of datapoints, computing one or more statistical measures based upon the aggregate data, and enabling querying of the subset of datapoints, the aggregate data, and the statistical measures computed for the first minute.

This specification provides a data disclosure method and apparatus. The data disclosure method includes: receiving a data disclosure request including a specified disclosure strategy and data to be disclosed; generating a disclosure task for the data to be disclosed according to the specified disclosure strategy; and calling the target channel to execute the disclosure task according to the configuration information of the target channel for the data to be disclosed included in the specified disclosure strategy. This enables the specified disclosure strategy and the data to be disclosed to be sent as a data disclosure request to a scheduling center when there is a disclosure requirement. The scheduling center can select and call different target channels for different data to be disclosed, thus achieving channel isolation when disclosing different data to be disclosed, thereby ensuring the security of data disclosure.