Federated deep learning for zero-day botnet attack detection in IoT-edge devices
Deep learning (DL) has been widely proposed for botnet attack detection in Internet of
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …
Anomaly detection in industrial IoT using distributional reinforcement learning and generative adversarial networks
Anomaly detection is one of the biggest issues of security in the Industrial Internet of Things
(IIoT) due to the increase in cyber attack dangers for distributed devices and critical …
(IIoT) due to the increase in cyber attack dangers for distributed devices and critical …
[HTML][HTML] Security of federated learning with IoT systems: Issues, limitations, challenges, and solutions
Abstract Federated Learning (FL, or Collaborative Learning (CL)) has surely gained a
reputation for not only building Machine Learning (ML) models that rely on distributed …
reputation for not only building Machine Learning (ML) models that rely on distributed …
FL-IIDS: A novel federated learning-based incremental intrusion detection system
Z **, J Zhou, B Li, X Wu, C Duan - Future Generation Computer Systems, 2024 - Elsevier
With the advantage of analyzing data of multiple work sites comprehensively while ensuring
data privacy, federated learning-based intrusion detection systems (IDS) are emerging as a …
data privacy, federated learning-based intrusion detection systems (IDS) are emerging as a …
[HTML][HTML] GöwFed: A novel federated network intrusion detection system
Network intrusion detection systems are evolving into intelligent systems that perform data
analysis while searching for anomalies in their environment. Indeed, the development of …
analysis while searching for anomalies in their environment. Indeed, the development of …