Generalizing intrusion detection for heterogeneous networks: A stacked-unsupervised federated learning approach
The constantly evolving digital transformation imposes new requirements on our society.
Aspects relating to reliance on the networking domain and the difficulty of achieving security …
Aspects relating to reliance on the networking domain and the difficulty of achieving security …
Adaptive intrusion detection in the networking of large-scale lans with segmented federated learning
Predominant network intrusion detection systems (NIDS) aim to identify malicious traffic
patterns based on a handcrafted dataset of rules. Recently, the application of machine …
patterns based on a handcrafted dataset of rules. Recently, the application of machine …
Federated learning for reliable model updates in network-based intrusion detection
Abstract Machine Learning techniques for network-based intrusion detection are widely
adopted in the scientific literature. Besides being highly variable, network traffic behavior …
adopted in the scientific literature. Besides being highly variable, network traffic behavior …
[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 …
Intrusion detection for softwarized networks with semi-supervised federated learning
With the increasing development of 5G/Beyond 5G and network softwarization techniques,
we have more flexibility and agility in the network. This can be exploited by Machine …
we have more flexibility and agility in the network. This can be exploited by Machine …
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 …
F-NIDS—A Network Intrusion Detection System based on federated learning
JA de Oliveira, VP Gonçalves, RI Meneguette… - Computer Networks, 2023 - Elsevier
The rise of IoT networks has presented fresh challenges in terms of scalability and security
for distributed Network Intrusion Detection Systems (NIDS) due to privacy concerns. While …
for distributed Network Intrusion Detection Systems (NIDS) due to privacy concerns. While …
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 …
FLUIDS: Federated Learning with semi-supervised approach for Intrusion Detection System
In this paper, we present FLUIDS, a Federated Learning with semi-sUpervised approach for
Intrusion Detection System. FLUIDS formulates the intrusion detection into a semi …
Intrusion Detection System. FLUIDS formulates the intrusion detection into a semi …
[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 …