A method of updating a neural network model by a terminal device, includes training a local model using a local data set collected by a terminal device to generate a trained local model; receiving, from a server, an independent identically distributed (i.i.d.) global data set, the i.i.d. global data set being a data set sampled for each class in a plurality of predefined classes; implementing the trained local model by inputting the i.i.d. global data set and transmitting final inference results of the implemented trained local model to the server; and receiving, from the server, a global model updated based on the final inference results of the inference.