… In summary, a federated learning scenario consists of two main phases: local update …
Federated Learning (HFL), Vertical Federated Learning (VFL), and Federated Transfer Learning (…

… existing works for intrusion detection in IoT, as well as the approaches for FL. Then, we
propose a privacy-preserving federated learning scheme for IoT intrusion detection, followed by a …

… intrusion detection method based on federated learning. … federated learning to the intrusion
detection model training of network traffic data. An intrusion detection federated learning …

… 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 …

The application of Machine Learning (ML) techniques to the well-known intrusion detection
systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks through an …

… This paper proposes a federated learning intrusion detection model called FedAGRU that
adopts to wireless edge networks. FedAGRU uses the computing resources of edge devices …

… In this paper, we propose a federated learning-based intrusion detection system, named
FELIDS, for securing agricultural-IoT infrastructures. Specifically, the FELIDS system protects …

… that circumvents IoT intrusion detection system using Federated Learning (FL). In this attack,
the attacker indirectly attacks FL-based IoT anomaly detection systems by controlling IoT …

… Multi-view learning has gained popularity for its ability to learn … a federated learning-based
intrusion detection approach, … data in a decentralized format to detect, classify, and defend …

… research existing approaches for intrusion detection based on federated learning in the context
of … This could help researchers in the field of intrusion detection to define their goals more …