27 results about "Data policy" patented technology

The invention belongs to the technical field of multi-dimensional data processing, and particularly relates to a policy recommendation-oriented multi-dimensional graph data recall policy system and method.The multi-dimensional graph data is cleaned and structured through data preprocessing, and the multi-dimensional graph data comprises enterprise portrait data, policy data and other related data; feature extraction: encoding the policy text by adopting a deep semantic analysis model, and extracting a feature vector containing context semantics; dynamic feature interaction: adjusting the importance of the user and policy features through a dynamic weight mechanism, and optimizing the feature interaction effect; multi-dimensional task collaboration: based on a multi-task learning framework, processing a plurality of policy objectives at the same time, and generating a comprehensive matching result; a recall strategy is generated, a multi-dimensional graph data recall strategy suitable for policy recommendation is generated in combination with the processing result, and real-time synchronization between a recommendation system and enterprise requirements and policy environment changes is ensured.

The invention discloses a distributed caching method and system and an acceleration method for large model reasoning service. The system comprises a confidential virtual machine cluster, a zero-trust distributed caching system and a FUSE client. The zero-trust distributed cache system comprises a data strategy service, a data engine plug-in, a distributed file system and a trusted access service. And the FUSE client is deployed at the confidential container end, and establishes secure connection with the trusted access service based on the remote proof and the identity legality confirmation proof of the corresponding confidential container so as to provide a plaintext data access service for the corresponding confidential container. According to the scheme, a distributed cache implementation scheme is provided for the confidential computing container cluster, and the problem of performance loss caused by repeatedly reading, encrypting and decrypting the same data from an external storage system is avoided while the data security is guaranteed by using the large-scale confidential container cluster; and the storage access efficiency in scenes such as model training and reasoning is improved.

The invention discloses a bridge engineering bidding and bidding quotation risk early warning and cost dynamic regulation and control system and method. The system comprises a data acquisition module, a data preprocessing module, a risk early warning module, a cost dynamic regulation and control module, a linkage execution module, a data storage and update module and a man-machine interaction module. On one hand, a multi-dimensional data acquisition system of bridge exclusive basic data, market dynamic data, policy and regulation data, bidding transaction data and construction pre-judgment data is covered, cooperative operation of static feature risk association factor extraction and dynamic time sequence risk change trend capture is realized, and the accuracy of risk assessment is improved; and meanwhile, a risk-cost closed-loop linkage mechanism is established, a cost-risk association database is constructed, and differential cost regulation and control strategies are formulated in combination with management and control targets of different stages of bidding and tendering, so that the technical problems of low regulation and control efficiency and poor adaptability are solved.

The invention discloses a data interaction method and system for attribute set deduplication and key abuse. The method comprises the following steps: generating a data strategy packet; uploading the data policy packet to a parallel chain, and performing attribute set de-duplication and policy encryption based on an intelligent contract of the parallel chain to obtain a reconstructed encrypted access policy; according to the reconstructed encryption access strategy, decryption and digital content encryption are carried out, and a combined ciphertext and an encrypted ciphertext are generated; the combined ciphertext and the encrypted ciphertext are stored in a cross-planet file module, and a corresponding IPFS link is obtained; the NIZK and the smart contract are cooperated to resist the problem of data leakage caused by key abuse between dishonest participating entities; and meanwhile, safe and efficient communication of cross-domain information is realized by a cross-chain interaction mechanism combining a relay chain and parallel chain collaborative cross-chain technology and HTLC (Hypertext Markup Language). According to the invention, a robust cross-domain digital content interaction mechanism is constructed, and rapid, safe and reliable exchange under diversified service scenes is ensured.

Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a decision tree to generate a recommended action in response to detecting a change in a data map representing a computing environment. The disclosed system determines relationships among data objects representing digital data, digital assets, and data processing activities and generates a data map according to the relationships. The disclosed system monitors the data map for changes and, responsive to determining a change in the data map, traverses a decision tree by executing one or more calls to one or more application programming interfaces according to the change in the data map and one or more data policies relevant to the changes. The disclosed systems utilize the decision tree and application programming interfaces to generate a recommended action for modifying digital assets, digital data, and / or data processing activities.

Techniques are described for managing data policy. An example wireless communication method includes transmitting, by a first device to a second device, a set of information comprising one or more data services provided by the first device, where the set of information is transmitted according to a rule.

The various implementations described herein include methods and systems of data governance. In one aspect, a method of purging backup data includes obtaining a database table having a corresponding data policy and generating an encrypted version of the database table by applying an encryption key, including encrypting at least a portion of the database table. The method further includes identifying an expiration date for the encryption key based on the data policy, and storing the encryption key, the expiration date, and an encryption identifier for the encryption key in an encryption table. The method also includes receiving a command to back up the database table and, in response to the command, generating a backup of the encrypted version of the database table. The method further includes storing the backup and, when a current date is at least the expiration date for the encryption key, deleting the encryption key.

The present application relates to the technical field of data processing, and provides an industry chain and innovation chain data processing method and device and electronic equipment. The method comprises: obtaining target data, the target data comprising industry research report data, industry data, innovation data, policy data and appeal data; generating an industry chain and innovation chain fusion graph according to industry nodes and innovation nodes in the industry research report data; constructing a node corpus of each industry node and each innovation node in the industry data and the innovation data according to the industry chain and innovation chain fusion graph; determining the strength and weakness levels of each node in the node corpus, and generating an industry and innovation fusion development strategy for the nodes according to the strength and weakness levels of each node and the target data. The embodiment of the present application can realize the convergence, governance and intelligent analysis of industry and scientific and innovative data, reduce the workload of industry chain and innovation chain fusion analysis, and empower the development of industry chain and innovation chain fusion through technical means.

A method of protecting networks may include detecting a compromised computing device associated with a security event generated by a unified security policy from a plurality of sites within a network. A context of the compromised computing device may be extracted. The context may be propagated to a controller. The method may further include fetching from an identity services engine (ISE), user identity associated with the compromised computing device, and provisioning the controller with a dynamic list and a data policy matching the dynamic list. The method may also include advertising the dynamic list and the data policy to at least one of the plurality7 of sites..

Methods, systems, and non-transitory computer readable storage media are disclosed for capturing, analyzing, and classifying network traffic data associated with a network communication between computing systems. For example, the disclosed systems execute operations to generate classifications of the content of the network traffic data utilizing a classification model. For example, the disclosed systems determine risk levels based on whether network traffic data transmitted within the transport layer of the network traffic data adheres to the requirements of the data policy. In certain aspects, the disclosed systems analyze captured network traffic data based a live network transmissions, logged network transmissions, an API specification, and / or API endpoints. In some aspects, the disclosed systems provide a classification analysis including risk levels associated with the network traffic data via a custom graphical user interface.

A system may include a network communication interface configured to receive network traffic, a processing unit, and a memory unit storing instructions for various engines that are executable by the processing unit. The various engines include a data policy enforcement engine that includes an intent detection engine configured to receive context data and content data relating to the network traffic and generate an intent indexer for the network traffic based on the context data and the content data. The intent indexer documents an operation request and a subject of the operation request that are connected to the network traffic. The various engines also include an intent policy control engine configured to administer aspects of the network traffic based on the intent indexer and the context data.

In an embodiment, a method of securing interaction with public large language models (LLMs) includes intercepting input data to a public LLM. The method also includes processing the input data based on a data policy applicable to the public LLM. The method also includes providing the processed input data to the public LLM. The method also includes intercepting output data from the public LLM that is responsive to the processed input data. The method also includes processing the output data based on the data policy applicable to the public LLM. The method also includes providing the processed output data to a requestor associated with the input data.

A plurality of data traffic patterns are generated based on call logs associated with previous data exchanges between a first microservice entity and a second microservice entity. It is determined based on a data policy that the second microservice entity is not authorized to consume a portion of the data exposed by the first microservice entity. In response, a first data traffic pattern of the plurality of data traffic patterns is identified that is associated with a first known data transfer or a first potential data transfer in which the second microservice entity consumes the portion of the data exposed by the first microservice entity. An alert associated with the first data traffic pattern is generated.

The invention discloses a consumer industry data set construction method and device and a medium. The method comprises the steps of obtaining multi-source data related to a consumer industry; the multi-source data comprises e-commerce platform public data, policy data, information data, public opinion data, macroeconomic data, industry data, consumption complaint data and consumption infrastructure data; establishing an association relationship among the data of the multi-source data on the basis of association elements; wherein the associated elements comprise a time dimension, a consumption subject and a consumption object; carrying out fusion processing on the multi-source data with the incidence relation; and based on the fused multi-source data, storing the fused multi-source data to a data warehouse by adopting a star model and / or a snowflake model. According to the method, an accurate consumer industry high-quality data set with clear data association is constructed.

Aspects discussed herein may relate to methods and techniques for scanning application programming interface requests and responses to more readily identify data issues. The system may aggregate one or more data requests and / or responses according to correlated data transactions between devices. The system may then analyze traffic associated with those requests to determine if the responses are consistent with data policies. If a response is out of line with such policies, a system for reporting and correction are described.

A query is received from an application. A data store is accessed and a set of data items are extracted from the data store based on the query. Access to the set of data items is provided to the sidecar process. Based on a criterion, the sidecar process causes the set of data items to be modified by at least one of adding additional information to the set of data items, deleting a data item from the set of data items, or altering a data item in the set of data items to generate a modified set of data items. The modified set of data items is provided to the application.

A data access device for enforcing a data policy, including an input unit, a processing unit, a data exposure enforcement unit, and an output unit, where the data access device is configured to run in a trusted execution environment; the input unit is configured to receive a first data including a request for handling data, and a target identification; the processing unit is configured to process the first data to attain a second data including the target identification and a data structure according to requirements of an application running in the data access device; the data exposure enforcement unit is configured to manipulate the second data according to a data exposure policy to attain a third data; and the output unit is configured to output the third data.

A method, system, and apparatus are provided for policy-based data management in an open radio access network (O-RAN) cloud (O-Cloud) infrastructure. The method may include storing, by an O-Cloud infrastructure, a data policy for managing a network function (NF) deployed on the O-Cloud infrastructure, the data policy including a definition for at least one action from among: an offload action, a remount action, and a notification action for notifying the NF of a security threat with respect to a data volume; and performing, by the O-Cloud infrastructure, the at least one action based on the data policy.

Methods, systems, and non-transitory computer readable storage media are disclosed for capturing, analyzing, and classifying network traffic data associated with a network communication between computing systems. For example, the disclosed systems execute operations to generate classifications of the content of the network traffic data utilizing a classification model. For example, the disclosed systems determine risk levels based on whether network traffic data transmitted within the transport layer of the network traffic data adheres to the requirements of the data policy. In certain aspects, the disclosed systems analyze captured network traffic data based a live network transmissions, logged network transmissions, an API specification, and / or API endpoints. In some aspects, the disclosed systems provide a classification analysis including risk levels associated with the network traffic data via a custom graphical user interface.

Methods and systems for secure, federated, and decentralized ownership, storage, sharing and usage of big data are provided. According to one example, a first server maintains access to a plurality of federated data sources including at least one local database and at least one remote database. The local database is subject to a first data policy controlled by the first server and the remote database is subject to a second data policy controlled by a remote server. The first server receives a query from a user electronic device and verifies at least one permission attribute of the user electronic device relative to the data policies. After the federated data operation query has been approved, the first server generates results of the query including data fields from the local and remote databases in compliance with the first and second data policies.

Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems to classify and modify digital content items to satisfy digital data requirements of data policies. For example, the content classification system validates, enforces, and remediates digital data content corresponding to digital data requirements of a data policy based on data types covered by the data policy. The disclosed systems generate classifications for digital content items by accessing digital content items and generating mappings between the digital content items and a data policy. The disclosed systems utilize the mappings and digital data requirements of the data policy to determine whether the digital content items violate one or more elements of the data policy. The disclosed systems can perform various downstream operations to remediate the data policy violations, such as by causing various computing devices to modify the violating digital content items.

Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems to classify and modify digital content items to satisfy digital data requirements of data policies. For example, the content classification system validates, enforces, and remediates digital data content corresponding to digital data requirements of a data policy based on data types covered by the data policy. The disclosed systems generate classifications for digital content items by accessing digital content items and generating mappings between the digital content items and a data policy. The disclosed systems utilize the mappings and digital data requirements of the data policy to determine whether the digital content items violate one or more elements of the data policy. The disclosed systems can perform various downstream operations to remediate the data policy violations, such as by causing various computing devices to modify the violating digital content items.

The application discloses a data interaction method and system for attribute set deduplication and key abuse, comprising: generating a data policy package; uploading the data policy package to a parallel chain, performing attribute set deduplication and policy encryption based on the smart contract of the parallel chain, and obtaining a reconstructed encrypted access policy; decrypting and encrypting digital content according to the reconstructed encrypted access policy to generate combined ciphertext and encrypted ciphertext; storing the combined ciphertext and the encrypted ciphertext to a cross-planet file module and obtaining the corresponding IPFS link; and cooperating with NIZK and the smart contract to complete the problem of resisting data leakage caused by key abuse between dishonest participating entities; meanwhile, the cross-chain technology and the cross-chain interaction mechanism combined with HTLC of the relay chain and the parallel chain are combined to realize efficient communication of cross-domain information security. The application builds a robust cross-domain digital content interaction mechanism to ensure fast, safe and reliable exchange in diversified service scenarios.

A plurality of data traffic patterns are generated based on call logs associated with previous data exchanges between a first microservice entity and a second microservice entity. It is determined based on a data policy that the second microservice entity is not authorized to consume a portion of the data exposed by the first microservice entity. In response, a first data traffic pattern of the plurality of data traffic patterns is identified that is associated with a first known data transfer or a first potential data transfer in which the second microservice entity consumes the portion of the data exposed by the first microservice entity. An alert associated with the first data traffic pattern is generated.

One example method includes identifying data to be shared by a first entity of an edge environment with a second entity of an edge environment, consulting a confidence score associated with the data, mapping the confidence score to a data policy, applying the data policy to the data, and enabling data policy-controlled access, by the second entity, to the data. The data policy specifies privacy and / or security requirements concerning the accessing and use of the data.

Data format drift protection for application programming interfaces is disclosed. Aspects discussed herein can involve methods and techniques for scanning application programming interface requests and responses to more easily identify data issues. A system can aggregate one or more data requests and / or responses according to related data transactions between devices. The system can then analyze traffic associated with those requests to determine whether responses comply with data policies. If responses do not comply with such policies, systems are described for reporting and correction.

The application discloses a kind of distributed cache method, system and acceleration method for big model inference service, system includes confidential virtual machine cluster, zero-trust distributed cache system, FUSE client;Zero-trust distributed cache system includes data policy service, data engine plug-in, distributed file system, trusted access service;FUSE client is deployed in confidential container end, and based on remote proof and corresponding confidential container identity legality confirmation proof and trusted access service establish secure connection, to provide clear text data access service to corresponding confidential container.This scheme provides a distributed cache implementation scheme for confidential computing container cluster, while ensuring data security by using large-scale confidential container cluster, avoids the performance loss problem caused by repeated reading and encryption and decryption of the same data to external storage system, realizes the improvement of storage access efficiency in model training and inference and other scenarios.