64 results about "Data disclosure" patented technology

The invention relates to the technical field of data processing, and discloses an electronic manufacturing intelligent production data set generation system based on multi-modal data fusion, and the system comprises a system module assembly which comprises a data collection layer, a data processing layer and a quality management layer. The invention further provides an electronic manufacturing intelligent production data set generation method based on multi-modal data fusion, and the method comprises the following steps: S1, multi-modal data collection: collecting data including enterprise business data, public compliance data, sensor data and video monitoring data; and S2, data preprocessing and labeling. Through a multi-modal data fusion technology, limitation of a single data type is broken through, cross-modal alignment and feature association of images, texts, sensor data and industrial identification data are realized, and the utilization rate of electronic manufacturing scene data is improved.

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 an evaluation method for dynamically calculating the quality degree based on a commercial network. The evaluation method comprises the following steps: acquiring multi-source heterogeneous commercial network data; wherein the commercial network data comprises enterprise internal data, public data and authorization data; performing data processing and integration on the multi-source heterogeneous commercial network data to obtain a commercial network knowledge graph; analyzing the commercial network knowledge graph by using a graph neural network to obtain an association mode between enterprises; performing risk quantification on the commercial network knowledge graph by using a risk quantification model to obtain a risk assessment result corresponding to the enterprise; and performing enterprise high-quality scoring by using the commercial network dynamic high-quality evaluation model in combination with the risk assessment result, the association mode and the commercial network knowledge graph. In this way, dependence on subject credit and static financial data can be reduced.

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.

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.

A method for storing and processing product carbon footprint data includes: identifying entities, relationships and attributes involved in the entire life cycle of a product, establishing a directed graph model of product carbon footprint data; encoding the product carbon footprint data of the entire life cycle in time and space, and structurally organizing the product carbon footprint data; constructing a storage record of product carbon footprint data based on a graph database, and making version marks for the generation, modification and update process of emission accounting data in the entire life cycle; establishing index keys based on entity tags according to dimensions such as emission process and space, and establishing an efficient retrieval method for the entire life cycle of product carbon footprint data; defining the scope of product carbon footprint disclosure, identifying important carbon footprint data nodes and relationships, and implementing integrated processing and transformation of product carbon footprint data to achieve mapping and visual expression from product carbon footprint data to disclosure reports. The present invention proposes a product carbon footprint data storage and processing solution based on a graph model, which realizes unified digital expression and full-process data management in product carbon footprint records, and realizes the disclosure and visualization of product carbon footprint data based on spatial information, thereby supporting application needs in fields such as carbon tax mechanisms, sustainable supply chains and sustainable finance.

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.

Methods, apparatus, systems and articles of manufacture are disclosed to project ratings for future broadcasts of media. Disclosed example methods include normalizing, with a processor, audience measurement data corresponding to media exposure data, social media exposure data and programming information associated with a future quarter to determine normalized audience measurement data. Disclosed example methods also include classifying a media asset based on the programming information to determine a media asset classification. Disclosed example methods also include building, with the processor, a projection model based on a first subset of the normalized audience measurement data, the first subset of the normalized audience measurement data associated with a first time frame relative to the future quarter, the first subset of the normalized audience measurement data based on the media asset classification, and applying, with the processor, the programming information to the projection model to project ratings for the media asset.

Aspects of the subject disclosure may include, for example, receiving information about a data flow for radio communication between the radio access network and user equipment, classifying the data flow as one of a large data flow and a small data flow, adjusting priority of the data flow by reducing relative priority of the data flow responsive to classifying the data flow as a large data flow, and communicating data including the data flow between the radio access network and the user equipment according to the adjusted priority. Other embodiments are disclosed.

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.

A method for receiving, at a VPN server, a first data request for the VPN server to retrieve first data of interest from a first host device; utilizing, by the VPN server, a first exit IP address to transmit a first query for retrieving the first data of interest; determining, by the VPN server based on transmitting the first query, that the first exit IP address is blocked by the first host device; suspending, by the VPN server based on determining that the first exit IP address is blocked by the first host device, utilization of the first exit IP address for retrieving the first data of interest from the first host device; and utilizing, by the VPN server, the first exit IP address to transmit a second query for retrieving second data of interest from a second host device is disclosed. Various other aspects are contemplated.

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 present invention relates to the technical field of energy management, and specifically provides an operation identification method and device for a user-side energy storage device. The method includes: obtaining the original data of a target enterprise and a control enterprise; wherein, the control enterprise has put an energy storage device into operation. Performing data processing on the original data to obtain the to-be-verified data of the target enterprise and the labeled data of the control enterprise. Inputting the labeled data into a clustering algorithm to output the clustering results before and after the energy storage device is put into operation. Obtaining the identification thresholds before and after the control enterprise puts the energy storage device into operation according to the clustering results. Identifying whether the target enterprise has put the energy storage device into operation according to the identification thresholds and the to-be-verified data. The present invention discovers the inherent structural characteristics of data unsupervised by introducing a clustering algorithm, providing support for the operation research of enterprise energy storage devices. It overcomes the limitation of data disclosure on energy storage operation identification, has good accuracy, and provides a basis for energy management and optimal scheduling.

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.

The invention relates to the technical field of energy management, and particularly provides an operation identification method and equipment for a user side energy storage device. The method comprises the following steps: acquiring original data of a target enterprise and a contrast enterprise; wherein the control enterprise is put into operation of the energy storage device. And performing data processing on the original data to obtain to-be-verified data of the target enterprise and annotation data of the contrast enterprise. And inputting the labeled data into a clustering algorithm, and outputting clustering results before and after the energy storage device is put into operation. And according to a clustering result, obtaining an identification threshold before and after the energy storage device is put into operation by the contrast enterprise. And identifying whether the target enterprise is put into operation of the energy storage device according to the identification threshold and the to-be-verified data. According to the method, the clustering algorithm is introduced to discover the internal structure characteristics of the data in an unsupervised manner, and support is provided for operation research of energy storage devices of enterprises. The limitation of data disclosure limitation on energy storage operation identification is overcome, the accuracy is good, and a basis is provided for energy management and optimal scheduling.

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.

A method for protecting against sensitive data disclosure includes receiving a user request to launch a web application in a web browser; loading code for the web application in the web browser; requesting session initialization from a web server; and receiving a dynamically and randomly generated URL map specific to a session from the web server, wherein the URL map identifies a plurality of randomly generated URL positions and for each URL position a randomly generated number of characters to skip. The method further includes modifying sensitive information associated with a URL in accordance with the URL map; transmitting the URL with the modified sensitive information to the web server; and receiving a requested data object from the web server, wherein the web server decoded the URL with the modified sensitive information to recover the sensitive information and used the decoded URL to access the data object.

The present invention relates to a method for selective disclosure of confidential data of a first user to a second user of a blockchain (450). The first user is equipped with a deterministic hierarchical key portfolio (410) and selects a leaf of the tree of the portfolio as an emitter account. A secret key is derived from the chain code of this emitter account and the data to be disclosed are encrypted using this secret key. The first user transmits, by means of a first transaction, the data encrypted in this manner to a smart contract (430) which stores them in the blockchain. It transmits by means of a second transaction an access credit to the smart contract which stores it in connection with the pair formed by the emitter account of the first user and the receiver account of the second user. The second user transmits a third transaction to the smart contract from its receiver account (420). If the credit is not zero, the smart contract makes available to the receiver account the encrypted data stored in the blockchain in connection with the emitter account of the first user.

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.

A method including receiving, at a VPN server from a user device, a data request for the VPN server to retrieve data of interest from a host device; transmitting, by the VPN server to the host device during the established VPN connection, a query to retrieve the data of interest based on utilizing a first exit IP address; and determining, by the VPN server based on transmitting the query, that the first exit IP address is blocked by the host device; retrieving, by the VPN server during the established VPN connection and based on determining that the first exit IP address is blocked by the host device, the data of interest based on utilizing a second exit IP address; and transmitting, by the VPN server to the user device during the established VPN connection, the data of interest retrieved based on utilizing the second exit IP address is disclosed.

The utility model provides a data announcement device for engineering management, which comprises a bottom plate, and rollers are fixedly mounted on the periphery of the bottom of the bottom plate; the supporting rods are fixedly installed at the two ends of the top of the bottom plate respectively, the outer side faces of the supporting rods are sleeved with sleeves, and limiting holes are formed in the supporting rods; the display board is fixedly mounted on the outer side surface of the sleeve; and the adjusting frame is fixedly mounted at the bottom of the display board. According to the data announcement device for engineering management provided by the utility model, through mutual cooperation of structures such as the bottom plate, the rollers, the supporting rods, the sleeves and the display plate, after the data announcement device is used, a user can move the display plate downwards to enable the sleeves to sleeve the outer side surfaces of the supporting rods, so that the occupied area of the announcement device is reduced, and the data announcement device is convenient to use. Therefore, a user can conveniently carry the announcement device after the engineering is finished.

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.