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 …
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 …
Line-speed and scalable intrusion detection at the network edge via federated learning
Intrusion detection through classifying incoming packets is a crucial functionality at the
network edge, requiring accuracy, efficiency and scalability at the same time, introducing a …
network edge, requiring accuracy, efficiency and scalability at the same time, introducing a …
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 …
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 …
[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 …
Federated learning for anomaly-based intrusion detection
MA Ayed, C Talhi - 2021 International Symposium on Networks …, 2021 - ieeexplore.ieee.org
We are attending a severe zero-day cyber attacks. Machine learning based anomaly
detection is definitely the most efficient defence in depth approach. It consists to analyzing …
detection is definitely the most efficient defence in depth approach. It consists to analyzing …
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 …
Intrusion detection with segmented federated learning for large-scale multiple lans
Traditional approaches to cybersecurity issues usually protect users from attacks after the
occurrence of specific types of attacks. Besides, patterns of recent cyberattacks tend to be …
occurrence of specific types of attacks. Besides, patterns of recent cyberattacks tend to be …