Beihang University

Hangzhou City University

Zhejiang Gongshang University

Xiling Luo

Siqi Ren

Song Han

Shuai Zhao

Minghui Wu

Luyao Wang

A privacy protection method and system for financial data sharing based on federated learning are provided. In recent years, due to the restrictions of data security and privacy protection laws and regulations, it is difficult to share data across institutions or departments. In order to make data transfer and transaction between different entities can be achieved without violating the national laws on data privacy and data security, the privacy protection method and system for financial data sharing based on federated learning is provided. A privacy collection intersection technology is adopted, so that two institutions, which may have many differences in business, but most of their customer groups are the same, jointly train a learning model.

Privacy protection method and system for financial data sharing based on federated learning

Growing community of inventors

Hangzhou, China

Xiling Luo