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 …

Research in the field of Intrusion Detection is focused on developing an efficient strategy that
can identify network attacks. One of the important strategies is to supervise the network …

Modern society has quickly evolved to utilize communication and data-sharing media with
the advent of the internet and electronic technologies. However, these technologies have …

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 …

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 …

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 …

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 …