Abstract: A method for federated data query includes: using, by a first electronic device, a joint query statement corresponding to a federated data query to obtain at least one operator containing a joint query operator; transforming the joint query operator to a first joint security operator; determining first data for intersection on the first electronic device by executing the first joint security operator, receiving second data for intersection from a second electronic device involved in the federated data query, and performing joint computing on the first data for intersection and the second data for intersection in a form of a ciphertext to obtain a joint data table; and determining a federated data query result corresponding to the at least one operator based on the joint data table.

Abstract: A method for federated data query includes: using, by a first electronic device, a joint query statement corresponding to a federated data query to obtain at least one operator containing a joint query operator; transforming the joint query operator to a first joint security operator; determining first data for intersection on the first electronic device by executing the first joint security operator, receiving second data for intersection from a second electronic device involved in the federated data query, and performing joint computing on the first data for intersection and the second data for intersection in a form of a ciphertext to obtain a joint data table; and determining a federated data query result corresponding to the at least one operator based on the joint data table.

Abstract: This application provides a federated-learning-based data processing method, apparatus, and device, and a computer-readable storage medium. The method includes obtaining data to be processed, the data to be processed comprising multiple object identifiers and a feature value corresponding to each object identifier; binning the data to be processed based on the feature value corresponding to each object identifier to obtain a number of bins; determining multiple target identifier sets from each bin, and transmitting each target identifier set to a label-party device; receiving each piece of set label distribution information corresponding to each target identifier set from the label-party device, and determining bin label distribution information corresponding to each bin based on each piece of set label distribution information; and merging bins based on a binning policy and each piece of bin label distribution information to obtain a final binning result.

Abstract: Provided is a method and system for uniform execution of feature extraction. The method comprises: acquiring a feature extraction script for defining a processing logic related to feature extraction; analyzing the feature extraction script to generate an execution plan for feature extraction; and executing the generated execution plan by a local machine or a cluster based on a feature extraction scene. Based on the method and system, feature extraction can be uniformly executed at various feature extraction scenes.