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

… 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 …

… 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, …

… -efficient on-device federated learning (FL)-based deep anomaly detection framework for …
edge devices to collaboratively train an anomaly detection model, which can improve its …

… 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 …

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

… 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 …

… We consider a horizontal federated learning system consisting of one … anomaly detection
model at the server to detect the anomalous clients and to eliminate their impact on federated …

… In conclusion, we implemented federated learning with the help of PyTorch and PySyft
using two datasets of Unsupervised Anomaly Detection Dataverse from Harvard Dataverse [11]. …