531 results about "Data provider" patented technology

The invention provides a credible sharing method and system for multi-party industrial data, and relates to the technical field of data processing, and the method comprises the steps that multiple participants encrypt local industrial data through a credible execution space, and generate encrypted data and corresponding data fingerprints; defining a data access rule based on the smart contract; verifying and auditing the data access request, and obtaining an encrypted data authorization certificate after verification and auditing; and under the federated learning framework, the trusted execution space of each data provider executes the privacy calculation task based on the authorization certificate, and outputs a task calculation result and sends the task calculation result to the task requester. According to the method and the device, the technical problem of privacy risk of data leakage or tampering caused by contradiction between multi-party industrial data sharing and privacy protection is solved, the privacy can still be ensured while data sharing is ensured through federated learning and trusted execution space, and the security and the credibility of data sharing are improved.

The invention discloses an urban multi-mode digital twin data asset security management method, and relates to the technical field of urban digital twin and data security, and the method comprises the steps: firstly building a unified access gateway, converging multi-department and multi-type data, and generating sensitivity annotation and privacy level metadata; performing differential privacy or desensitization and dynamically calibrating parameters at the local part of the data provider according to the labels; bookkeeping access, authorization and training on a permission alliance chain, and performing fine-grained permission control; through on-chain authorization, each node only uploads disturbed and encrypted model update, and a global model is obtained after secure aggregation; the governance layer continuously monitors logs, budget and model indexes and triggers strategy closed-loop regulation and control; and multi-agent reinforcement learning of a privacy agent and a performance agent is further introduced, a unified multi-target optimizer is formed through distillation, privacy, federation and permission strategies are refreshed online, and collaborative analysis and compliance sharing operation without data out of a domain are realized.

The embodiment of the invention provides a credit scoring method and device for a credit white user. Wherein the data provider comprises a government affair platform party, a transaction opposite party and a financial institution party, and the user data of the financial institution party comprises a user identifier of a credit white user. And the plurality of data providers align the local user data of each party through a privacy intersection algorithm, so that each party determines the first user data of the aligned credit white user from the local user data. And the plurality of data providers respectively encrypt the local first user data of each party and send the encrypted first user data to the service platform. And the service platform performs secret state model prediction based on a local credit scoring model and the first encrypted user data of each party, obtains a secret state credit score of the credit white user, and provides the secret state credit score to a score user. And the score user decrypts the credit score from the secret state credit score, and determines a risk control decision for the credit white user based on the credit score.

The invention discloses a data exchange method and device for a trusted data space and a medium. The method comprises the following steps: establishing a verifiable registry and a distributed digital steward of a trusted data space; registering a data space main body ID for each main body of the trusted data space, and signing and issuing an identity certificate for each main body based on the data space main body ID; according to the identity credentials and the private keys of all the main bodies, identity mutual recognition among all the main bodies is achieved, and an incidence relation is established; writing metadata required by the data provider or the data developer to publish data into a verifiable registry, and establishing a data space data ID of the metadata based on the data space main body ID of the data publisher and the metadata; connection is established among distributed digital housekeepers, an end-to-end encryption connection pipeline is formed, and encryption data exchange is completed based on a connection channel.

The invention discloses an auditing key management method based on a trusted execution environment, which comprises the following steps that: a data provider encrypts original data by using k to obtain a ciphertext C, and calculates a hash value id of the C; t; id, kgt; storing the result in association locally, and storing the result; d, Cgt; uploading to a cloud server; the data provider formulates and signs a data use strategy, the data processor formulates and signs a data processing strategy, and the data use strategy and the data processing strategy are both sent to the security service program of the trusted execution environment; verifying the signature and the authorization state of the processing strategy, and sending a key request and a remote authentication report to a data provider; after the data provider remotely verifies the remote report, if the request is agreed, the key k is sent to the security service program through the security channel, and a key use record is stored in the block chain; and the security service program downloads the ciphertext C, decrypts the data after verification, executes processing operation, and returns an encryption result to a specified receiver. According to the invention, real-time auditing and evidence storage can be carried out on the use process of the secret key, and cross-domain management and control of data can be realized.

The invention discloses a data security sharing method and system, and relates to the technical field of data sharing. The method comprises the steps that a data provider uploads original data, a privacy budget value is calculated through a differential privacy algorithm, noise is added to obtain noisy data, and the noisy data is processed through an anonymous privacy protection algorithm based on maximum dissimilarity degree clustering to obtain desensitized data; encrypting the desensitized data by adopting a block chain decentralization-based ciphertext policy attribute-based encryption method, obtaining an encrypted data ciphertext, uploading the encrypted data ciphertext to a cloud server, and obtaining a content addressing hash value; encrypting the hash value through an elliptic curve encryption algorithm, and storing the encrypted hash value to a block chain account book; and when an access request of a data requester is received, the cloud server verifies the authority by using a non-interactive zero-knowledge proof protocol and returns an encrypted hash value after passing the verification, and the requester decrypts to obtain the hash value and decrypts the encrypted ciphertext to obtain desensitized data, thereby realizing data sharing.

The invention discloses a large model corpus data interaction system and method based on a trusted execution environment, a terminal and a medium. The system comprises a data provider, a data demander and a trusted data space service platform. And the data provider is used for encrypting the corpus data, and performing preprocessing, directory sorting and packaging on the corpus data in the data provider connector to obtain the data capsule. And the data demander is used for submitting a calculation task in the data demander connector and obtaining corpus data of the data capsule for calculation after authorization. And the trusted data space service platform is used for storing the encrypted corpus data, controlling access of a data user, scheduling a calculation task, managing a key and generating an audit log. Through trusted execution environment hardware isolation and full-link encryption, it is ensured that corpus data only exists in a plaintext form in the trusted execution environment in the full life cycle from access to destruction, and unauthorized access and leakage are completely eradicated.

The invention discloses a trusted data sharing method based on a block chain consensus mechanism. The method comprises the following steps: S1, constructing an alliance chain network; s2, completing KZG polynomial commitment generation, ML-KEM algorithm encryption storage and pointer registration; s3, the data provider medical institution completes an evidence storage transaction of the FROST threshold signature; s4, the target medical institution completes the access request transaction; s5, the data provider medical institution sends a KZG unpacking proof and a data item, the target medical institution obtains a storage pointer and a commitment value, KZG verification check is executed, and after verification is passed, an ML-KEM algorithm is executed for depacking to obtain a session key; and S6, the target medical institution completes the audit transaction, and after the alliance chain network broadcast, the consensus node executes rule verification of the access control contract and the audit contract. The multi-node electronic medical record sharing and tamper-proof evidence storage method is high in performance and traceability, and is suitable for credible circulation of sensitive health data among multiple medical institutions.

The invention provides a data capsule generation and verification method and device, equipment and a medium. The method is applied to a data sending end, and comprises the following steps: determining an encryption key and an access strategy corresponding to a data provider; performing encryption processing on the to-be-encrypted data based on the encryption key to obtain encrypted data, and determining a first encryption parameter corresponding to the encrypted data according to the encrypted data and an access policy; based on the first encryption parameter and the identity information, adopting a preset calculation rule to generate a capsule identifier corresponding to the to-be-encrypted data; and packaging the capsule identifier, the access strategy, the encrypted data and a preset calculation rule to obtain a corresponding data capsule. According to the scheme, the verifiable and non-tampering capsule identifier is generated based on the encrypted data, the access strategy and the identity information, so that the risks of data packet switching, content replacement, strategy tampering and the like are effectively prevented, and the structural security and the use control credibility of the data capsule are improved.

The invention discloses a data fine-grained access control method, system and device and a medium, mainly relates to the technical field of access control, and is used for solving the problems of identity and attribute separation, low strategy updating efficiency and insufficient auditing capability in the existing scheme. Comprising the steps that a data user generates a distributed digital identity document containing at least one role attribute through a distributed digital identity system, and the distributed digital identity document is subjected to uplink storage after being audited by a registration mechanism; the data provider generates an ABE private key according to the main public key and an access control strategy, encrypts the ABE private key by using the DID public key of the data user, and sends the encrypted ABE private key to the data user; the data user obtains an ABE private key by using the DID private key; decrypting the ABE ciphertext on the block chain by using the ABE private key to obtain a symmetric key; and obtaining the original data in the trusted data space through symmetric key decryption.

An example method includes determining a provider distribution by television viewing area using a provider-reported number of subscribers for a television viewing area and a sum of weights of panelist households that are located within the television viewing area. The method also includes obtaining a target distribution of a characteristic for the television viewing area. In addition, the method includes determining, using iterative proportional fitting, provider-specific distributions of the characteristic for the television viewing area. And the method includes using the provider-specific distributions of the characteristic for the television viewing area as a basis for assigning values of the characteristic to households that are subscribers of the return path data provider and located in the television viewing area.

The invention discloses a data circulation method and device in a trusted data space, equipment and a medium, and relates to the technical field of data security sharing, and the method comprises the steps: obtaining a node instance request sent by a data demander through a first connector node in the trusted data space; wherein the data demander accesses the trusted data space through the first connector node; responding to the node instance request to determine a data flow path between the first connector node and a second connector node in the trusted data space, so that the data provider transmits to-be-transmitted target data to the data demander through the data flow path; wherein the data provider accesses the trusted data space through the second connector node. According to the invention, secure transmission and sharing of data in a trusted data space are realized.

Systems and methods for watermarking machine learning training data for verification thereof, include, for a training data provider, obtaining training data; responsive to verifying the training data based on a use case or application associated therewith, watermarking the training data by adding watermarked data therein; and publishing the watermarked training data. For a machine learning model provider, the systems and methods include obtaining training data to train the machine learning model for an application or use case, to any of make predictions, inferences, and classifications related to the application or use case; obtaining a one-way function associated with the application or use case; checking the training data with the one-way function to determine validity thereof; and, responsive to the validity, utilizing the training data to train the machine learning model.

Disclosed in the present application are a data access control method and device based on semantic support, and a medium. The method comprises: a data provider establishing an ontology model of data semantics on the basis of ontology knowledge of each piece of distributed data source data, and uploading the ontology model to a blockchain network; providing rule information of the data source data, and writing a distributed data source data address and the rule information into a smart contract on the blockchain network, wherein the rule information is used for representing an access control policy for the distributed data source data; receiving a data access request uploaded by a data access end by means of the blockchain network, and acquiring authorization information for the data access request on the basis of the rule information in the smart contract; and if it is determined that the authorization information indicates that access is allowed, on the basis of a data access method corresponding to the ontology model, acquiring fine-grained data corresponding to the data access request, encrypting the fine-grained data, and then sending same to the data access end.

The invention relates to the technical field of data processing, and provides an API calling method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: receiving an API access request sent by a data provider; analyzing a request parameter in the API access request to obtain at least one request field and a field value corresponding to each request field; determining a request entry parameter based on each request field, the field value corresponding to each request field and the data type of each field value; calling a target API of the data receiver based on the request incoming parameter, so as to send the request incoming parameter to the data receiver; the request input parameter is used for indicating the data receiver to execute the service logic matched with the request input parameter. According to the method and the device, time does not need to be wasted in connection adaptation of the data provider and the downstream data receiver, that is, the low-code integration platform only needs to analyze the API access request to automatically generate the request entry parameter capable of calling the target API, so that API calling is quickly realized, and the API calling efficiency is improved.

The embodiment of the invention discloses a data space and a data interaction method. The data space comprises a plurality of modules, and an efficient intelligent data circulation system is constructed. The data market platform stores data resource description, and the data resource library is responsible for storing data governance information. And the AIAgent module converts query of a data demander into a structured request through a natural language processing technology, and performs data matching. And a matching result generates a data use protocol through the contract management module, so that the data use compliance is ensured. And the user interaction module is used for displaying and confirming protocol content and ensuring consensus of a data provider and a data demander. Once confirmed by the protocol, the data resource description will be delivered to the data demander through the AIAgent delivery engine. According to the invention, the data interaction and delivery efficiency is greatly improved, manual intervention is reduced, intelligent scheduling, development and utilization of data resources are realized, and data transaction circulation is effectively promoted.

An example operation may include one or more of receiving, at a data provider, a data file from a data modifier which comprises a modification to an initial content state of a data file, generating a hash value of the initial content state of the data file prior to modification and generating a hash value of a modified content state of the data file after the modification, and transmitting the generated hash values to a blockchain peer node for inclusion within one or more data blocks among a hash-linked chain of data blocks.

The embodiment of the invention provides a structured data field use control method and device, a medium and a product, and relates to the technical field of data use. The method comprises the steps of obtaining a data product published by a data provider; the data product is formed by accessing structured data into a data space in a data source form by a data provider; binding a target strategy generated based on the structured data to the data product, and determining a bound target data product; the target strategy comprises a post strategy and a calculation strategy executed at a first trusted connector of the data user, and a pre strategy executed at a second trusted connector of the data provider; and performing data contract signing with the data provider according to the target data product. The method is based on a structured data form, and is more accurate than traditional privacy calculation control; the target strategy and the data product are directly bound, and a traditional strategy configuration mode based on a central server is replaced.

The invention discloses a port wave spectrum parametric modeling algorithm based on machine learning, and relates to the technical field of ocean engineering, and high-precision modeling is realized through three steps: step one, constructing a federated learning framework, training sub-models by data parties only sharing parameters, combining homomorphic encryption fusion features and dynamically adjusting weights, and constructing a model; privacy protection type data fusion is realized; a second step of deploying a generative adversarial network at each local node, extracting multi-scale wave features through a frequency domain hierarchical attention branch network, implanting a sea wave energy conservation constraint and optimizing a generator, generating an extreme sample conforming to a physical law, and forming a mixed training data set; and a third step of training a CNN-LSTM basic model, and realizing dynamic optimization of the model through a sliding window, a forgetting factor, Bayesian optimization and performance monitoring reconstruction. The method effectively improves the wave spectrum prediction precision and long-term stability, reduces the maintenance cost, and can be used for scenes such as port ship berthing and disaster prevention early warning.

Determining when and / or how to execute a program or script published to a blockchain network may rely on data that is external to the blockchain (i.e., external data) such as data about the real-world state and events. A prover (e.g., a node of the blockchain network) may perform one or more computations on behalf of a client, such as the execution of the program. To execute the program properly, the prover may rely on external data, which the prover may obtain from a data provider that has a trust relationship with the client (e.g., the client accepts as valid data provided by a trusted data provider). Systems and methods described herein may be utilized by a prover to provide cryptographically verifiable assurances of the authenticity of input data purportedly obtained from a data provider, the input data utilized in the execution of a program or script published to a blockchain network. An example of a blockchain network is a Bitcoin-based network.

The invention discloses a data use control method and system based on a smart contract, and relates to the technical field of data use control, and the system comprises an identity authentication module, a data classification and grading module, a data sandbox module and an evidence storage traceability module. Performing identity authentication on a user request of a data user based on an authentication protocol; performing classification rating on the accessed data; the data user and the data provider negotiate a contract signing detailed rule; the data user and the data provider sign a block chain smart contract; deploying the intelligent contract to a data sandbox, performing authority evaluation and distribution on the user, and performing behavior monitoring on the user; when the data user violates the signed smart contract, terminating the data access permission of the user, and calling the data sandbox to execute operation according to the contract signing content; logs are automatically generated, data access and use circulation are traced in the whole process, and it is ensured that data can be traced, audited and managed from authorization to use. According to the invention, the security and credibility of data circulation are guaranteed in a data transmission use control mode with decentration and multi-party cooperative participation.

The invention relates to the technical field of data product pricing, and discloses a data pricing method based on multi-dimensional value evaluation, a terminal and a storage medium. The method comprises the steps of performing desensitization processing on data needing to be priced based on a differential privacy mechanism, generating a privacy budget value and a privacy risk value of the data, and obtaining a privacy score according to the privacy budget value and the privacy risk value; generating a quality score of the data according to the evaluation index of the desensitized data on the specified task; calculating a dynamic weight coefficient meeting the optimal privacy budget value by using a dual-objective optimization algorithm, wherein the dynamic weight coefficient is used for balancing a privacy protection objective and a data quality objective; and based on the privacy score, the quality score, the dynamic weight coefficient and the cost information of the data provider, generating a data pricing formula by using a meta-learning model, and outputting a pricing result. According to the invention, fair and reasonable data pricing is realized, the expectation of the data purchaser for the data and the leakage risk of the data provider are balanced, and the healthy development of the data transaction market is promoted.

The invention relates to the technical field of data processing, and discloses a data exchange method, system and device based on a block chain and computer equipment. The method comprises the following steps: establishing a block chain environment through a network, generating an identification code and a key pair, and constructing a resource directory tree; performing standardization processing on the data, calculating data fingerprints, and constructing an exchange packet and a list; constructing an intelligent contract based on the identification code, and forming a deployment record; generating a transaction request, and verifying by adopting a PBFT algorithm to obtain a block proof; generating an access token to realize data synchronization; and executing integrity verification, and generating a right and interest distribution result. According to the method, on the premise that the data security and credibility are guaranteed, controllable sharing and fair exchange of the data are achieved, and meanwhile it is guaranteed that the rights and interests of a data provider are reasonably guaranteed.

In an embodiment, a method provides an environment for privately exchanging data for AI tasks. Identification of a task to perform, and a characteristic describing data needed to execute the task, is received. A data provider within the environment is located that has access to a data set according to the characteristic. A task provider within the environment is located. The located task provider is configured to execute the task. A real-time, private, and secure network connection between the data provider and the task provider is established. The established connection is configured such that the data provider and the task provider are able to communicate via the network connection without using publicly accessible network addresses. The data set is transferred from the data provider to the task provider via the established network connection. In response to the transfer, the task provider executes the task using the data set.

The invention discloses a meteorological data source credibility proving method based on a block chain, and provides a new data source credibility proving mechanism by utilizing the characteristics of tamper resistance, forgery resistance and loss resistance of the block chain and combining signature verification and hash operation algorithms in cryptography. According to the mechanism, credibility and data delivery validity verification can be accurately carried out on delivery data recorded by a data provider; according to the patent, transaction / shared data is converted into a pre-agreed intermediate format (a character set, a coding mode and an XML / JSON data structure expression mode) and is stored in a file form. And after receiving the data, the data user converts the data into a self system format according to self system requirements, so that the correctness of data information expression is ensured. Through the overall transmission of the data packet, the accidental missing and tampering of the data in the transmission process between the two handover parties are effectively avoided.

The invention discloses a data processing method and device, a medium, equipment and a product. According to the scheme, after the data platform receives the data processing request sent by the data demander, the encrypted first privacy data set can be determined according to the data processing request, and the privacy data set can be processed based on the user data adopted by at least one data provider. The method comprises the following steps: acquiring a first private data set, acquiring a second private data set encrypted by adopting an encryption mode of encrypting the first private data set, comparing the first private data set with the second private data set to obtain an intersection data set, and further returning a service result for a specified service to a data demander based on the obtained intersection data set.

Provided in the present disclosure are a data circulation method and apparatus, and a first platform and a first node. The method comprises: a first platform receiving information which is related to a data resource and is sent by a first node; and the first platform adding to a global data directory the information related to the data resource, wherein the first node is a trusted computing node of a data provider, and the first platform is a data scheduling center platform.

The invention provides a financial big data information processing system based on a block chain. The financial big data information processing system based on the block chain comprises a block chain network access module used for accessing financial institution nodes and data provider nodes to an alliance chain network and synchronizing distributed account books among the nodes through a Byzantine fault-tolerant consensus algorithm so as to realize tamper-proof evidence storage and multi-party trust cooperation of financial big data information. According to the financial big data information processing system based on the block chain, through homomorphic encryption, zero-knowledge proof and other technologies, operation and verification of data in an encryption state are ensured, privacy of sensitive information is effectively protected, and data sharing and calculation can be smoothly carried out while confidentiality is ensured.

The invention provides an exception handling method and device, a storage medium, electronic equipment and a product. The exception handling method is applied to a credit investigation system corresponding to a credit investigation mechanism, and comprises the following steps: receiving a data query request for target data sent by a data demand side, and querying the target data from a data provider according to the data query request; processing the target data returned by the data provider to obtain a processing result; if the data processing result is successful, credit investigation data obtained after the target data is processed is returned to the data demander; if the data processing result is failure, determining a failure type causing data processing failure based on an abnormal state code carried in the data processing result, and triggering an exception processing flow matched with the failure type; wherein different abnormal state codes correspond to different failure types, and the failure types comprise service side failures caused by inconformity with service rules and system side failures caused by abnormity of the credit investigation system.