TRANSACTION REQUEST CONSTRUCTION METHOD AND APPARATUS, TRANSACTION REQUEST PROCESSING METHOD AND APPARATUS, DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20220100777A1

    公开(公告)日:2022-03-31

    申请号:US17548680

    申请日:2021-12-13

    Inventor: Bo JING

    Abstract: Provided are a transaction request construction method and apparatus, a transaction request processing method and apparatus, a device and a storage medium, which relate to the field of blockchain technology and can be used for cloud computing and cloud services. A specific implementation includes: generating a standard transaction request according to a standard key of a service application party, to-be-processed request data, a target blockchain architecture to be accessed and a target blockchain identifier; and calling a transaction conversion service and converting the standard transaction request into a target transaction request under the target blockchain architecture according to the standard key, the target blockchain architecture and the target blockchain identifier; where the target transaction request is used for processing the to-be-processed request data. Transaction request construction and processing efficiency can be improved.

    TRAINING METHOD AND APPARATUS FOR A NEURAL NETWORK MODEL, DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20230186049A1

    公开(公告)日:2023-06-15

    申请号:US18077361

    申请日:2022-12-08

    Inventor: Bo JING

    CPC classification number: G06N3/04 H04L9/008

    Abstract: Provided are a training method and apparatus for a neural network model, a device and a storage medium. The training method includes: acquiring a first feature representation ciphertext of a sample user from a first party; determining the tag ciphertext of the sample user and determining the loss error ciphertext and the gradient ciphertext of a second neuron in a second sub-neural network based on the second sub-neural network according to the first feature representation ciphertext and the tag ciphertext; controlling the first party to decrypt the gradient ciphertext of the second neuron to obtain a decryption result and updating the network parameter of the second neuron according to the decryption result acquired from the first party; and sending the loss error ciphertext of an association neuron to the first party.

    METHOD FOR TRAINING MODEL BASED ON HOMOMORPHIC ENCRYPTION, DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20230188321A1

    公开(公告)日:2023-06-15

    申请号:US18080416

    申请日:2022-12-13

    Inventor: Bo JING

    CPC classification number: H04L9/008

    Abstract: Provided are a method for training a model based on homomorphic encryption, a device, and a storage medium. The specific implementation is: acquiring homomorphic encrypted data in a model training process; determining a hyperparameter of a model approximation function according to state data present in the model training process, where the model approximation function is used for replacing a model original function involved in the model training process; and inputting the homomorphic encrypted data to the model approximation function for calculation, and performing model training according to a calculation result. Therefore, the application flexibility of functions is improved while achieving the protection of data privacy in the model training process.

    TRAINING METHOD AND APPARATUS FOR NEURAL NETWORK MODEL, DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20230186102A1

    公开(公告)日:2023-06-15

    申请号:US18077471

    申请日:2022-12-08

    Inventor: Bo JING

    CPC classification number: G06N3/098

    Abstract: Provided are a training method and apparatus for a neural network model, a device and a storage medium. the training method includes: acquiring a feature representation ciphertext of a sample user from each feature provider of at least two feature providers separately; and determining the loss error ciphertext and the gradient ciphertext of a tag neuron in a tag sub-neural network based on the tag sub-neural network according to the feature representation ciphertext and a tag ciphertext; controlling the each feature provider to decrypt the gradient ciphertext of the tag neuron to obtain a decryption result and updating the network parameter of the tag neuron according to the decryption result acquired from the each feature provider; and sending the loss error ciphertext of an association neuron to the each feature provider.

    TRAINING METHOD AND APPARATUS FOR A DISTRIBUTED MACHINE LEARNING MODEL, DEVICE AND MEDIUM

    公开(公告)号:US20230078726A1

    公开(公告)日:2023-03-16

    申请号:US17932405

    申请日:2022-09-15

    Inventor: Bo JING

    Abstract: Provided are a training method and apparatus for a distributed machine learning model, a device and a medium. The training method includes: acquiring a first homomorphic encryption intermediate parameter and a second homomorphic encryption intermediate parameter; generating a first interference parameter, and forming a first encryption interference parameter by encrypting the first interference parameter by using a second homomorphic public key of a second participant; performing calculation based on the first homomorphic encryption intermediate parameter, the second homomorphic encryption intermediate parameter, the first encryption interference parameter and the homomorphic calculation function of a first submodel to generate a first encryption key parameter.

Patent Agency Ranking