Network anomaly detection is a critical aspect of network management for instance for QoS,
security, etc. The continuous arising of new anomalies and attacks create a continuous …

Most traditional network anomalies and attacks detection systems tend to employ supervised
strategies, which require labeled training dataset that is arduous and expensive to obtain …

Network anomaly detection has been a hot research topic for many years. Most detection
systems proposed so far employ a supervised strategy to accomplish the task, using either …

Current network monitoring systems rely strongly on signa-ture-based and supervised-
learning-based detection methods to hunt out network attacks and anomalies. Despite being …

Network anomalies and attacks represent a serious challenge to ISPs, who need to cope
with an increasing number of unknown events that put their networks' integrity at risk. Most of …

Anomaly detection has become a vital component of any network in today's Internet.
Ranging from non-malicious unexpected events such as flash-crowds and failures, to …

Network anomaly detection aims to detect patterns in a given network traffic data that do not
conform to an established normal behavior. Distinguishing different anomaly patterns from …

Anomaly detection is a crucial topic in network security which refers to automatically mining
known and unknown attacks or threats. Many detectors have been proposed in the last …

Cross domain data such as numerical or categorical types are ubiquitous in practical
network. Network anomaly detection based on cluster analysis exist some difficulties, for …

Nowadays, network intrusion detectors mainly rely on knowledge databases to detect
suspicious traffic. These databases have to be continuously updated which requires …