Advanced New Technologies Co., Ltd.

Alibaba Group Holding Limited

Pengfei Ying

Lichun Li

Zheng Liu

Shan Yin

Huazhong Wang

A query request is forwarded to a plurality of service provider servers by a proxy server that determines a serial number based on the query request. An encrypted query result corresponding to the query request is received from each service provider server, and a copy of the encrypted query result is stored as a result to be audited in a blockchain that associated with each service provider server. An audit request is sent to at least one service provider server. The result to be audited is obtained from the blockchain corresponding to the service provider server. As a standard result, an encrypted query result is received from the service provider server. As an audit, the standard result received from the service provider server is compared with the result to be audited that obtained from the blockchain that associated with the service provider server.

Data auditing method and device

Privacy protection methods, systems, and apparatus, including computer programs encoded on computer storage media, are provided. One of the methods is performed by a first computing device and includes: obtaining a plurality of object IDs, wherein the plurality of object IDs include a target object ID; sending the plurality of object IDs to a second computing device storing a plurality of pieces of data respectively associated with the plurality of object IDs for the second computing device to generate a plurality of ciphertexts respectively based on the plurality of pieces of data; and executing a cryptography protocol with the second computing device to obtain a ciphertext corresponding to the target object ID from the plurality of ciphertexts generated by the second computing device, wherein the target object ID is unknown to the second computing device.

Method and apparatus for obtaining input of secure multiparty computation protocol

A method for protecting user privacy for a privacy protection application, includes: receiving a request for user data of a user from a third-party service; receiving, from the user, an authorization for the request for the user data; acquiring the user data from a plurality of different storage facilities; processing the acquired user data with a data model provided by the third party service, wherein the data model comprises a multi-party computation model configured to generate processed user data based on the user data stored at the plurality of different storage facilities; encrypting the processed user data using a third-party public key associated with the third-party service; and transmitting the encrypted processed user data to the third-party service to enable the third-party service to decrypt the encrypted processed user data to obtain the processed user data.

Distributed personal data storage and encrypted personal data service based on secure computation

Techniques for providing a data request method are described. A data request is received from a user requesting a calculation. In response to receiving the data request, an inquiry message is transmitted to a plurality of service nodes. A confirmation message is received from each service node from the plurality of service nodes, wherein the confirmation message comprises data indicating whether a service node will participate in the requested calculation or will not participate in the requested calculation. A contribution of the service node is determines based on the confirmation message. A resource is allocated to each service node that will participate in the requested calculation.

Dynamically-organized system for distributed calculations

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a multi-party secure logistic regression model (SLRM). One of the methods includes receiving, at a plurality of secure computation nodes (SCNs), a plurality of random numbers from a random number provider; encrypting, at each SCN, data stored at the SCN using the received random numbers; iteratively updating a secure logistic regression model (SLRM) by using the encrypted data from each SCN; and after iteratively updating the SLRM, outputting a result of the SLRM, wherein the result is configured to enable a service to be performed by each SCN.

Growing community of inventors

Hangzhou, China

Pengfei Ying