Method for improving user authentication performed by a communication device

Abstract

Method for improving user authentication efficiency performed by a communication device belonging to an authentication system. The communication device includes a local machine learning engine having a set of N artificial neural network ANNadapted to process N different types of input signals. The method includes the steps: receiving a first set of N input signals S_() for authentication purpose; determining respectively for each of the N input signals S_() by the N artificial neural networks ANN, N estimations LH(i) of the likelihood that a given input signal is provided by a legitimate user; determining based on a risk scoring established using the N estimations LH(i) if the requesting user is authenticated as the legitimate user; if the requested user is authenticated, determining if at least one likelihood estimation determined for a given input signal S_() is below a predetermined threshold T, and if it is the case: transmitting the input signal S_() to a remote server implementing a server machine learning engine adapted to process said N different types of input signals and trained to identify a user U_C; receiving an input signal S_() associated to the closest candidate U_C and executing by the local machine learning engine an additional learning phase using the input signal S_() as an input signal that is not associated to the requesting user.