Intrusions in computer networks have increased significantly in the last decade, due in part
to a profitable underground cyber-crime economy and the availability of sophisticated tools …

The rapid growth of the Internet and communications has resulted in a huge increase in
transmitted data. These data are coveted by attackers and they continuously create novel …

The popularity of using Internet contains some risks of network attacks. Intrusion detection is
one major research problem in network security, whose aim is to identify unusual access or …

Since the early days of research on intrusion detection, anomaly-based approaches have
been proposed to detect intrusion attempts. Attacks are detected as anomalies when …

A popular approach for detecting network intrusion attempts is to monitor the network traffic
for anomalies. Extensive research effort has been invested in anomaly-based network …

Zero-day cyber attacks such as worms and spy-ware are becoming increasingly widespread
and dangerous. The existing signature-based intrusion detection mechanisms are often not …

The use of Machine Learning (ML) techniques in Intrusion Detection Systems (IDS) has
taken a prominent role in the network security management field, due to the substantial …

The use of deep learning models for the network intrusion detection task has been an active
area of research in cybersecurity. Although several excellent surveys cover the growing …

Automatic network intrusion detection has been an important research topic for the last
20years. In that time, approaches based on signatures describing intrusive behavior have …

The growing prevalence of network attacks is a well-known problem which can impact the
availability, confidentiality, and integrity of critical information for both individuals and …