This project pursues research advances in the TRUSTED (DECENTRALIZED) FEDERATED LEARNING, (D)FL, area, that jointly addresses the challenges of privacy, security and robustness for distributed learning systems by combining information theory techniques, post-quantum encryption, crypto-coded computation and adversarial machine learning. Additionally, and since the INCIBE projects also have an important social aspect, TRUFFLES proposes some dissemination and social awareness activities