Skip to main content

Scientific Reports (Nature Publishing Group) IoT Datasets...

Showing 2 of 2 datasets

Clear Filters
Scientific Reports (Nature Publishing Group)
IoT Security / Machine Learning Intrusion Detection Feb 03, 2026

Securing IoT Networks: A Machine Learning Approach for Detecting Unusual Traffic Patterns

A merged and optimized dataset combining N-BaIoT (IoT-specific traffic) and UNSW-NB15 (general network threats) with feature engineering, dimensionality reduction, and benchmarked ML models (Decision Tree, SVM, Random Forest, Neural Network) for IoT anomaly detection, published in Scientific Reports.

#N-BaIoT #UNSW-NB15 #IoT security #machine learning +6 more
Scientific Reports (Nature Publishing Group)
IoT Network Security / Federated Learning Feb 03, 2026

Dataset-Centric Evaluation of Federated Intrusion Detection Models in IoT Networks

A federated learning evaluation across several contemporary IoT and IIoT intrusion detection datasets, benchmarking algorithms such as FedAvg, FedProx, and FedNova with LSTM and Transformer models in in-domain, cross-dataset, and multi-dataset federation scenarios.

#federated learning #intrusion detection #IoT security #dataset evaluation +7 more