Federated learning for internet of things: Recent advances, taxonomy, and open challenges
… 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 …
federated learning towards enabling federated learning-… taxonomy for federated learning over …
Federated learning for internet of things: A comprehensive survey
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, …
of intelligent services and applications empowered by artificial intelligence (AI). Traditionally, …
Federated learning for the internet of things: Applications, challenges, and opportunities
… -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. …
of federated learning for IoT. We … research at the intersection of federated learning and IoT. …
Recent advances on federated learning for cybersecurity and cybersecurity for federated learning for internet of things
… 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, …
… mechanism for data collaborations in the Internet of Things,” IEEE Internet Things J., vol. 7, …
Internet of things intrusion detection: Centralized, on-device, or federated 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 …
intrusion detection that maintains data privacy by performing local training and inference of …
Federated learning for internet of things
… malicious participants poison the federated model. However… federated learning algorithmic
framework, FedDetect which utilizes adaptive optimizer (eg, Adam) and cross-round learning …
framework, FedDetect which utilizes adaptive optimizer (eg, Adam) and cross-round learning …
[HTML][HTML] Evaluating Federated Learning for intrusion detection in Internet of Things: Review and challenges
… 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 …
use of Federated Learning (FL) has attracted a significant interest in different sectors, including …
Local differential privacy-based federated learning for internet of things
… 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 …
facilitate the crowdsourcing applications to achieve the machine learning model. Specifically, we …
Federated learning for vehicular internet of things: Recent advances and open issues
… 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 …
purpose of collaborative learning … In this paper we use FL to denote the federated learning with …
End-to-end evaluation of federated learning and split learning for internet of things
… , 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) and split neural network (SplitNN) (also referred to as split learning…
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