The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation
of intelligent services and applications empowered by artificial intelligence (AI). Traditionally, …

… -preserving nature of federated learning makes it well suited … on some important applications
of federated learning for IoT. We … research at the intersection of federated learning and IoT. …

… learning, it has still privacy concerns. In this paper, first, we present the recent advances of
federated learning towards enabling federated learning-… taxonomy for federated learning over …

… malicious participants poison the federated model. However… federated learning algorithmic
framework, FedDetect which utilizes adaptive optimizer (eg, Adam) and cross-round learning …

… In this context, we propose in this article a Federated Learning based scheme for IoT
intrusion detection that maintains data privacy by performing local training and inference of …

… article, we propose to integrate federated learning and local differential privacy (LDP) to
facilitate the crowdsourcing applications to achieve the machine learning model. Specifically, we …

… federation of the learned and shared model on top of various participants. Federated learning
… mechanism for data collaborations in the Internet of Things,” IEEE Internet Things J., vol. 7, …

… To mitigate privacy concerns associated with centralized approaches, in recent years the
use of Federated Learning (FL) has attracted a significant interest in different sectors, including …

… , and text inputs) during the learning process to reduce privacy … learning techniques, namely
federated learning (FL) and split neural network (SplitNN) (also referred to as split learning…

… Federated learning (FL) is a distributed machine learning approach that can achieve the
purpose of collaborative learning … In this paper we use FL to denote the federated learning with …