公开(公告)号：US20230418794A1

公开(公告)日：2023-12-28

申请号：US18252926

申请日：2021-11-06

Applicant: Lemon Inc.

Inventor： Chenliaohui FANG ,  Junyuan XIE ,  Lele YU ,  Xiaobing LIU ,  Di WU

IPC: G06F16/215 ,  G06F21/60

CPC classification number: G06F16/215 ,  G06F21/602

Abstract: The present disclosure relates to a data processing method, non-transitory medium and electronic device. The method includes: acquiring first user data and second user data, and initializing a first time window corresponding to the first user data and first time information corresponding to the first time window, as well as a second time window corresponding to the second user data and second time information corresponding to the second time window; determining first data and the first time information corresponding to the first time window based on the first user data; determining second data and the second time information corresponding to the second time window based on the second user data; based on the first data and the second data, determining alignment data corresponding to a same user from the first user data and the second user data.

公开(公告)号：US20230418470A1

公开(公告)日：2023-12-28

申请号：US18252982

申请日：2021-11-15

Applicant: LEMON INC.

Inventor： Liangchao WU ,  Junyuan XIE ,  Lizhe ZHANG ,  Di WU ,  Xiaobing LIU

IPC: G06F3/06

CPC classification number: G06F3/0604 ,  G06F3/0638 ,  G06F3/0683

Abstract: Disclosed in the embodiments of the present disclosure are a data processing method and apparatus, and an electronic device. A specific implementation of the method comprises: determining a target first storage region from among a preset number of first storage regions; on the basis of a interaction process with a second device, determining identical target identification information comprised in the target first storage region and a target second storage region, and determining whether the interaction process meets a target requirement; and in response to the interaction process meeting the target requirement, storing target first data identified by the target identification information, so that the second device stores target second data identified by the target identification information. Thus, the target first data and the target second data identified by the same target identification information in the target first storage region and the target second storage region are aligned.

公开(公告)号：US20240249004A1

公开(公告)日：2024-07-25

申请号：US18565000

申请日：2022-04-28

Applicant: Lemon Inc.

Inventor： Xin YANG ,  Jiankai SUN ,  Weihao GAO ,  Junyuan XIE ,  Chong WANG

IPC: G06F21/60 ,  G06N20/20

CPC classification number: G06F21/602 ,  G06N20/20

Abstract: The present disclosure relates to a method and a device for data protection, a readable medium and an electronic apparatus, and the method comprises: acquiring a target identification information union set, wherein the target identification information union set comprises target encryption identification information of a first party of a joint training model and target encryption identification information of a second party of the joint training model, the target encryption identification information in the target identification information union set being obtained by encrypting according to a secret key of the first party and a secret key of the second party; and determining, according to the target identification information union set, a target sample data set for training the joint training model. Therefore, an identification information intersection of the first party and the second party does not need to be determined in advance as in the related technology.

公开(公告)号：US20240220641A1

公开(公告)日：2024-07-04

申请号：US18565962

申请日：2022-07-15

Applicant: Lemon Inc.

Inventor： Jiankai SUN ,  Xin YANG ,  Aonan ZHANG ,  Weihao GAO ,  Junyuan XIE ,  Chong WANG

IPC: G06F21/60 ,  G06N20/00

CPC classification number: G06F21/602 ,  G06N20/00

Abstract: The present disclosure relates to a data protection method, apparatus, medium and electronic device. The method comprises: obtaining a specified batch of reference samples of an active participant of a joint training model; determining generation gradient information of the first reference sample; determining target gradient information sent to the passive participant according to the generation gradient information, and sending the target gradient information to the passive participant, to update, by the passive participant, parameters of the joint training model according to the target gradient information. Through the above solution, the influence of the generated data on the training process and model performance of the joint training model is avoided as much as possible, and the privacy and security of data are improved.

公开(公告)号：US20240126899A1

公开(公告)日：2024-04-18

申请号：US18539851

申请日：2023-12-14

Applicant: Lemon Inc.

Inventor： Xin YANG ,  Junyuan XIE ,  Jiankai SUN ,  Yuanshun YAO ,  Chong WANG

IPC: G06F21/62 ,  G06N3/04 ,  G06N3/098

CPC classification number: G06F21/62 ,  G06N3/04 ,  G06N3/098

Abstract: There are proposed a method, device, apparatus, and medium for protecting sensitive data. In a method, to-be-processed data is received from a server device. A processing result of a user for the to-be-processed data is received, the processing result comprising sensitive data of the user for the processing of the to-be-processed data. A gradient for training a server model at the server device is determined based on a comparison between the processing result and a prediction result for the to-be-processed data. The gradient is updated in a change direction associated with the gradient so as to generate an updated gradient to be sent to the server device. Noise is added only in the change direction associated with the gradient. The corresponding overhead of processing noise in a plurality of directions can be reduced, and no excessive noise data interfering with training will be introduced to the updated gradient.

公开(公告)号：US20240242089A1

公开(公告)日：2024-07-18

申请号：US18565015

申请日：2022-04-28

Applicant: Lemon Inc.

Inventor： Jiankai SUN ,  Weihao GAO ,  Junyuan XIE ,  Chong WANG

IPC: G06N3/098 ,  G06N3/04

CPC classification number: G06N3/098 ,  G06N3/04

Abstract: The present disclosure relates to a data protection method, a training method and apparatus for a network structure, a medium, and a device. The data protection method includes: obtaining original feature information of a target batch of reference samples for a passive party of a joint training model; and processing the original feature information by means of a target feature processing network structure to obtain target feature information corresponding to the original feature information. A neural network structure is trained by at least aiming at minimizing a coupling degree of between original training feature information and target training feature information of training samples for the passive party to obtain the target feature processing network structure. The target training feature information is feature information corresponding to the original training feature information that is outputted from the neural network structure using the original training feature information as an input.

公开(公告)号：US20240012641A1

公开(公告)日：2024-01-11

申请号：US18252942

申请日：2021-11-16

Applicant: Lemon Inc.

Inventor： Ruoxing HUANG ,  Junyuan XIE ,  Longyijia LI ,  Chenliaohui FANG ,  Shihao SHEN ,  Lei SHI ,  Lingyuan ZHANG ,  Peng ZHAO ,  Deliang FAN ,  Di WU ,  Xiaobing LIU

IPC: G06F8/71 ,  H04L9/40 ,  G06N3/098 ,  G06F16/955

CPC classification number: G06F8/71 ,  H04L63/101 ,  G06N3/098 ,  G06F16/9558

Abstract: A model construction method and an apparatus, and a medium and an electronic device are disclosed. The method is applied to a first participant platform, and includes: associating first configuration information pre-created by a first participant with second configuration information pre-created by a second participant; verifying the first configuration information; sending, to a second participant platform corresponding to the second participant, a second creation request for requesting the creation of the federated learning model, to cause the second participant platform to verify the second configuration information creating a first model task on the basis of a first parameter corresponding to the first configuration information; and performing co-training on the basis of the first model task and a second model task, to obtain the federated learning model.