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

Abstract Network Anomaly Detection Systems (NADSs) are gaining a more important role in
most network defense systems for detecting and preventing potential threats. The paper …

With the growing processing power of computing systems and the increasing availability of
massive datasets, machine learning algorithms have led to major breakthroughs in many …

The implementation of electronics in modern vehicles has resulted in an increase in attacks
targeting in-vehicle networks; thus, attack detection models have caught the attention of the …

Neural networks have become an increasingly popular solution for network intrusion
detection systems (NIDS). Their capability of learning complex patterns and behaviors make …

With the advent of the Internet of Things (IoT), the security of the network layer in the IoT is
getting more and more attention. The traditional intrusion detection technologies cannot be …

In recent years, machine learning-based intrusion detection systems (IDSs) have proven to
be effective; especially, deep neural networks improve the detection rates of intrusion …

Distributed denial-of-service is one kind of the most highlighted and most important attacks
of today's cyberworld. With simple but extremely powerful attack mechanisms, it introduces …

In the present world huge amounts of data are stored and transferred from one location to
another. The data when transferred or stored is primed exposed to attack. Although various …

Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data
mining and statistics literature. In most applications, the data is created by one or more …