With the rapid growth and the increasing complexity of network infrastructures and the
evolution of attacks, identifying and preventing network abuses is getting more and more …

The continuous increase in the number of attacks on computer networks has raised serious
concerns regarding the importance of establishing a methodology that can learn and adapt …

A great deal of attention has been given to deep learning over the past several years, and
new deep learning techniques are emerging with improved functionality. Many computer …

Anomaly detection in communication networks provides the basis for the uncovering of
novel attacks, misconfigurations and network failures. Resource constraints for data storage …

Network traffic anomaly detection is an important technique of ensuring network security.
However, there are usually three problems with existing machine learning based anomaly …

In recent years, network anomaly detection has become an important area for both
commercial interests as well as academic research. Applications of anomaly detection …

Networks of various kinds often experience anoma-lous behaviour. Examples include
attacks or large data transfers in IP networks, presence of intruders in distributed video …

Network intrusion detection is a key pillar towards the sustainability and normal operation of
information systems. Complex threat patterns and malicious actors are able to cause severe …

In this article the emphasis is placed on the evaluation of the impact of intelligent flow
sampling techniques on the detection and classification of network anomalies. Based on the …

With the rapid rise in the ubiquity and sophistication of Internet technology and the
accompanying growth in the number of network attacks, network intrusion detection has …