Method and device for controlling electronic device for federated learning

Abstract

Embodiments of the disclosure relate to an electronic device and a server for federated learning, and a method of the same. A method of refining a core artificial intelligence (AI) model built in the server includes transmitting, to each of a plurality of electronic devices performing federated learning with the core AI model, data for requesting transmission of first data used for refining the core AI model, receiving first data from at least one of the plurality of electronic devices, identifying an electronic device that has transmitted the first data from among the plurality of electronic devices, transmitting data for requesting transmission of second data to the electronic device that has transmitted the first data among the plurality of electronic devices, receiving second data from the electronic device that has transmitted the first data, and refining the core AI model by using the first data and the second data, wherein the first data includes first differential privacy protection data for protecting private data of each of the plurality of electronic devices, and the second data includes differential privacy modification data used to modify the first differential privacy protection data into second differential privacy protection data.