SECURE MULTI-PARTY COMPUTATION METHODS AND APPARATUSES

    公开(公告)号:EP4262134A1

    公开(公告)日:2023-10-18

    申请号:EP23167642.0

    申请日:2023-04-12

    IPC分类号: H04L9/00

    摘要: Embodiments of this specification provide computer-implemented methods, apparatuses, computer-readable media and systems for secure multi-party computation. According to an example computer-implemented method, a first party performs a first mapping operation and homomorphic encryption on first plaintext data to obtain a first converted ciphertext in a Montgomery state, where the first mapping operation converts data from an integer ring to the Montgomery state. The first party sends the first converted ciphertext to a second party. Then, the second party performs a first homomorphic operation in the Montgomery state based on the first converted ciphertext to obtain a first result ciphertext in the Montgomery state, where the first homomorphic operation includes a modular multiplication operation.

    METHOD AND APPARATUS FOR JOINT TRAINING LOGISTIC REGRESSION MODEL

    公开(公告)号:EP4254227A1

    公开(公告)日:2023-10-04

    申请号:EP23166033.3

    申请日:2023-03-31

    发明人: CUI, Jinming WANG, Li

    IPC分类号: G06F17/18 G06N20/00 H04L9/08

    摘要: Some embodiments of this specification provide methods for jointly training a logistic regression model. The training includes three types of training data: a sample characteristic, a sample label, and a model parameter, each of which is split into fragments that are distributed between two parties. The method is performed by either first party of the two parties, and includes: performing masking on three first-party fragments corresponding to the three types of training data by respectively using first fragments of three random numbers in a first fragment of a random array to obtain three first mask fragments, and sending the three first mask fragments to a second party, where the first fragment of the random array is a fragment, sent by a third party to the first party, of two-party fragments that are obtained by splitting values in the random array generated by the third party; constructing three pieces of mask data corresponding to the three types of training data by using the three first mask fragments and three second mask fragments received from the second party; and performing a first calculation based on the three pieces of mask data and the first fragment of the random array to obtain a first gradient fragment for updating the first-party fragment of the model parameter.

    DATA DETERMINATION METHODS, APPARATUSES, STORAGE MEDIA, AND TERMINAL DEVICES

    公开(公告)号:EP4262140A1

    公开(公告)日:2023-10-18

    申请号:EP23168142.0

    申请日:2023-04-15

    摘要: This specification discloses data determination methods, apparatuses, storage media, and terminal devices. The method includes: A first terminal device sends first encrypted data to a second terminal device; the second terminal device encrypts the first encrypted data by using a second public key to obtain second encrypted data, and sends the second encrypted data and third encrypted data to the first terminal device; the first terminal device encrypts the third encrypted data by using a first public key to obtain fourth encrypted data, acquires first intersection data of the second encrypted data and the fourth encrypted data, and sends the first intersection data to a third terminal device; the third terminal device acquires fifth encrypted data sent by the first terminal device; the third terminal device determines second intersection data based on the fifth encrypted data and the first intersection data, and sends the second intersection data to the first terminal device and the second terminal device.