Alipay (hangzhou) Information Technology Co., Ltd.

Alipay Information Technology Co., Ltd.

Jinming Cui

Lei Wang

Jun Zhou

Li Wang

Lei Zhang

Chaochao Chen

Jian Du

Yufei Lu

Pu Duan

Hongjun Yin

Yilun Lin

Methods, apparatuses, and systems for protecting privacy are described. In an example, a first party encrypts a first data set, and sends a single-encrypted full data set to a second party. The second party re-encrypts the single-encrypted full data set to obtain a double-encrypted full data set, obtains a single-encrypted sampling data set, and sends the single-encrypted sampling data set to the first party. The first party encrypts the single-encrypted sampling data set to obtain a double-encrypted sampling data set, determines an intersection of the double-encrypted full data set and the double-encrypted sampling data set, performs upsampling on a complement other than the intersection in the double-encrypted sampling data set to obtain a noise-added intersection, and sends an element index of the noise-added intersection to the second party. The second party determines related information of common data based on the element index.

Common data determining methods, apparatuses, and systems for protecting privacy

A computer-implemented method, medium, and system are disclosed. One example method includes determining multiple model bases by multiple service parties. A respective local service model is constructed by each service party. Respective local training samples are processed by each service party using the respective local service model to determine respective gradient data corresponding to each model basis. The respective gradient data is sent to a server. In response to determining that the first model basis satisfies a gradient update condition, corresponding gradient data of the first model basis received from each service party are combined to obtain global gradient data corresponding to the first model basis. The global gradient data is sent to each service party. Reference parameters in local model basis corresponding to the first model basis are updated by each service party using the global gradient data to train the respective local service model.

Methods, apparatuses, and systems for updating service model based on privacy protection

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Hangzhou, China

Jinming Cui