The invention belongs to the technical field of
artificial intelligence, and relates to a combined
deep learning training method based on a
privacy protection technology. The efficient combined
deep learning training method based on the
privacy protection technology is achieved. In the invention, each participant first trains a local model on a private
data set to obtain a local gradient, then performs Laplace
noise disturbance on the local gradient, encrypts the local gradient and sends the encrypted local gradient to a
cloud server; The
cloud server performs aggregation operation on all thereceived local gradients and the
ciphertext parameters of the last round, and broadcasts the generated
ciphertext parameters; And finally, the participant decrypts the received
ciphertext parameters and updates the local model so as to carry out subsequent training. According to the method, a
homomorphic encryption scheme and a
differential privacy technology are combined, a safe and efficient
deep learning training method is provided, the accuracy of a training model is guaranteed, and meanwhile a
server is prevented from inferring
model parameters, training data privacy and internal attacksto obtain private information.