Data encryption method, federal modeling method and device and computer equipment

Abstract

The invention provides a data encryption method, a federal modeling method, a federal modeling device and computer equipment, and the method comprises the steps: generating an RSA public and private key pair, and transmitting an RSA public key to a second client; obtaining second encrypted data obtained by performing blind operation on a second user ID by the second client based on the RSA public key; using an RSA private key to sign a first user ID to obtain first encrypted data, performing blind signature on the second encrypted data to obtain third encrypted data, and sending the first encrypted data and the third encrypted data to the second client; obtaining a random number set generated by the second client based on the first encrypted data and the third encrypted data; and performing mapping association on the random number set and first encrypted data. In the privacy intersection process of the two interaction parties, encryption operation is carried out for multiple times, and the risk that the intersection ID and internal data of the two interaction parties are leaked is effectively reduced through random number processing.

Description

technical field [0001] The invention relates to the technical field of data encryption, in particular to a data encryption method, a federated modeling method, a device and computer equipment. Background technique [0002] With the rapid development of machine learning, machine learning has been applied in various fields. Especially for some special scenarios, it is necessary to apply machine learning to protect the intersection ID of both parties, and model based on this premise. For example, an insurance company has insurance product purchase data of most users in the industry, and another insurance company hopes to establish a precise marketing model based on internal customer data to predict whether the company's internal customers will purchase specified insurance products. The data cannot be modeled. At this time, it is necessary to conduct federated learning modeling with companies that have most of the user insurance product purchase data in the industry. [0003] ...

AI Technical Summary

Problems solved by technology

[0004] Therefore, the technical problem to be solved by the present invention is to overcome the problem of leaking the intersection ID of both parties when performin

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