… propose federated learning (FL)-based anomaly detection approach to proactively recognize
intrusion in IoT networks using decentralized on-device data. Our approach uses federated …

… Moreover, most of the previous works focus on one specific task of anomaly detection, …
neural network in federated learning (MT-DNN-FL) to perform network anomaly detection task, …

… federated learning (FL)-based deep anomaly detection frame… to collaboratively train an
anomaly detection model, which … -LSTM) model to accurately detect anomalies. The AMCNN-…

… and federated learning approaches for anomaly detection in a … In Section 3, we present our
federated learning system as … a novel federated learning architecture for anomaly detection in …

… We present a solution where contributing parties in federated learning can be held …
federated learning method where incremental updates to an anomaly detection machine learning …

… design a decentralized IoT anomaly detection framework, in which … secure and accurate IoT
anomaly detection. The main … asynchronous federated learning-based IoT anomaly detection …

… a reliable anomaly detection strategy for IIoT using federated learning. Specifically, we
apply the federated learning technique to build a universal anomaly detection model with each …

… the performance of most network traffic anomaly detection methods, which have low accuracy
… personalized federated anomaly detection framework for network traffic anomaly detection, …

… An anomaly detection architecture for the IIoT-based SM is … - a Federated Learning architecture
- that can detect anomalies for … detection performance compared to the current detection …

… Federated Learning (FL) with mobile computing and the Internet of Things (IoT) is an
effective cooperative learning approach. However, several technical challenges still need to be …