Recent endeavors in machine learning-powered intrusion detection systems for the Internet of Things
D Manivannan - Journal of Network and Computer Applications, 2024 - Elsevier
The significant advancements in sensors and other resource-constrained devices, capable
of collecting data and communicating wirelessly, are poised to revolutionize numerous …
of collecting data and communicating wirelessly, are poised to revolutionize numerous …
Bad Design Smells in Benchmark NIDS Datasets
R Flood, G Engelen, D Aspinall… - 2024 IEEE 9th European …, 2024 - ieeexplore.ieee.org
Synthetically generated benchmark datasets are vitally important for machine learning and
network intrusion research. When producing intrusion datasets for research, providers make …
network intrusion research. When producing intrusion datasets for research, providers make …
Strengthening Network Intrusion Detection in IoT Environments with Self-supervised Learning and Few Shot Learning
Abstract The Internet of Things (IoT) has been introduced as a breakthrough technology that
integrates intelligence into everyday objects, enabling high levels of connectivity between …
integrates intelligence into everyday objects, enabling high levels of connectivity between …
FedMADE: Robust Federated Learning for Intrusion Detection in IoT Networks Using a Dynamic Aggregation Method
The rapid proliferation of Internet of Things (IoT) devices across multiple sectors has
escalated serious network security concerns. This has prompted ongoing research in …
escalated serious network security concerns. This has prompted ongoing research in …