Fed-anids: Federated learning for anomaly-based network intrusion detection systems
As computer networks and interconnected systems continue to gain widespread adoption,
ensuring cybersecurity has become a prominent concern for organizations, regardless of …
ensuring cybersecurity has become a prominent concern for organizations, regardless of …
Multi-task network anomaly detection using federated learning
Because of the complexity of network traffic, there are various significant challenges in the
network anomaly detection fields. One of the major challenges is the lack of labeled training …
network anomaly detection fields. One of the major challenges is the lack of labeled training …
An enhanced AI-based network intrusion detection system using generative adversarial networks
C Park, J Lee, Y Kim, JG Park, H Kim… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
As communication technology advances, various and heterogeneous data are
communicated in distributed environments through network systems. Meanwhile, along with …
communicated in distributed environments through network systems. Meanwhile, along with …
An efficient federated learning system for network intrusion detection
Network intrusion detection is used to detect unauthorized activities on a digital network,
with which the cybersecurity teams of organizations can then kick-start prevention protocols …
with which the cybersecurity teams of organizations can then kick-start prevention protocols …
Pelican: A deep residual network for network intrusion detection
One challenge for building a secure network communication environment is how to
effectively detect and prevent malicious network behaviours. The abnormal network …
effectively detect and prevent malicious network behaviours. The abnormal network …
[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 …
Federated learning-based network intrusion detection with a feature selection approach
Y Qin, M Kondo - 2021 International conference on electrical …, 2021 - ieeexplore.ieee.org
With the increase and diversity of network attacks, machine learning has shown its efficiency
in realizing intrusion detection. Federated Learning (FL) has been proposed as a new …
in realizing intrusion detection. Federated Learning (FL) has been proposed as a new …
Security and privacy-enhanced federated learning for anomaly detection in IoT infrastructures
Internet of Things (IoT) anomaly detection is significant due to its fundamental roles of
securing modern critical infrastructures, such as falsified data injection detection and …
securing modern critical infrastructures, such as falsified data injection detection and …
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 …
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 …