[HTML][HTML] Evaluating Federated Learning for intrusion detection in Internet of Things: Review and challenges
Abstract The application of Machine Learning (ML) techniques to the well-known intrusion
detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks …
detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks …
F-bids: Federated-blending based intrusion detection system
The rapid development of network communication along with the drastic increase in the
number of smart devices has triggered a surge in network traffic, which can contain private …
number of smart devices has triggered a surge in network traffic, which can contain private …
A review of federated learning in intrusion detection systems for iot
Intrusion detection systems are evolving into intelligent systems that perform data analysis
searching for anomalies in their environment. The development of deep learning …
searching for anomalies in their environment. The development of deep learning …
An ensemble multi-view federated learning intrusion detection for IoT
The rise in popularity of Internet of Things (IoT) devices has attracted hackers to develop IoT-
specific attacks. The microservice architecture of IoT devices relies on the Internet to provide …
specific attacks. The microservice architecture of IoT devices relies on the Internet to provide …
The evolution of federated learning-based intrusion detection and mitigation: a survey
In 2016, Google introduced the concept of Federated Learning (FL), enabling collaborative
Machine Learning (ML). FL does not share local data but ML models, offering applications in …
Machine Learning (ML). FL does not share local data but ML models, offering applications in …
[HTML][HTML] Clustered federated learning architecture for network anomaly detection in large scale heterogeneous IoT networks
There is a growing trend of cyberattacks against Internet of Things (IoT) devices; moreover,
the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse …
the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse …
Semisupervised federated-learning-based intrusion detection method for internet of things
Federated learning (FL) has become an increasingly popular solution for intrusion detection
to avoid data privacy leakage in Internet of Things (IoT) edge devices. Existing FL-based …
to avoid data privacy leakage in Internet of Things (IoT) edge devices. Existing FL-based …
Hierarchical federated learning for collaborative IDS in IoT applications
As the Internet-of-Things devices are being very widely adopted in all fields, such as smart
houses, healthcare, and transportation, extremely huge amounts of data are being gathered …
houses, healthcare, and transportation, extremely huge amounts of data are being gathered …
Internet of things intrusion detection: Centralized, on-device, or federated learning?
With the ever increasing number of cyber-attacks, internet of Things (ioT) devices are being
exposed to serious malware, attacks, and malicious activities alongside their development …
exposed to serious malware, attacks, and malicious activities alongside their development …
A federated learning-based approach for improving intrusion detection in industrial internet of things networks
MM Rashid, SU Khan, F Eusufzai, MA Redwan… - Network, 2023 - mdpi.com
The Internet of Things (IoT) is a network of electrical devices that are connected to the
Internet wirelessly. This group of devices generates a large amount of data with information …
Internet wirelessly. This group of devices generates a large amount of data with information …