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 …
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 …
Deep learning-enabled anomaly detection for IoT systems
Abstract Internet of Things (IoT) systems have become an intrinsic technology in various
industries and government services. Unfortunately, IoT devices and networks are known to …
industries and government services. Unfortunately, IoT devices and networks are known to …
Federated deep learning for anomaly detection in the internet of things
X Wang, Y Wang, Z Javaheri, L Almutairi… - Computers and …, 2023 - Elsevier
Privacy has emerged as a top worry as a result of the development of zero-day hacks
because IoT devices produce and transmit sensitive information through the regular internet …
because IoT devices produce and transmit sensitive information through the regular internet …
Blockchain for federated learning toward secure distributed machine learning systems: a systemic survey
Federated learning (FL) is a promising decentralized deep learning technology, which
allows users to update models cooperatively without sharing their data. FL is reshaping …
allows users to update models cooperatively without sharing their data. FL is reshaping …
[HTML][HTML] Federated learning for generating synthetic data: a scoping review
Objectives The objective was to review current research and practices for using FL to
generate synthetic data and determine the extent to which research has been undertaken …
generate synthetic data and determine the extent to which research has been undertaken …
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 …
[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 …
FL-IIDS: A novel federated learning-based incremental intrusion detection system
Z Jin, 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 …