Nowadays, there is a huge and growing concern about security in information and
communication technology among the scientific community because any attack or anomaly …

Anomaly detection has numerous applications in diverse fields. For example, it has been
widely used for discovering network intrusions and malicious events. It has also been used …

Abstract Information technology has penetrated into all aspects of politics, economy, and
culture of the whole society. The information revolution has changed the way of …

Bot detection using machine learning (ML), with network flow-level features, has been
extensively studied in the literature. However, existing flow-based approaches typically incur …

Intrusion detection systems are devoted to monitor a network with aims at finding and
avoiding anomalous events. In particular, we focus on misuse detection systems, which are …

In today's cyber world, the Internet has become a vital resource for providing a plethora of
services. Unavailability of these services due to any reason leads to huge financial …

Detecting intrusion in network traffic has remained a problem for years. Development in the
field of machine learning provides an opportunity for researchers to detect network intrusion …

Feature engineering and selection is a critical step in the implementation of any machine
learning system. In application areas such as intrusion detection for cybersecurity, this task …

Intrusion detection is becoming a hot topic of research for the information security people.
There are mainly two classes of intrusion detection techniques namely anomaly detection …

Intrusion detection systems are used for monitoring the network data, analyze them and find
the intrusions if any. The major issues with these systems are the time taken for analysis …