Due to the very fast growth of computer networks, Internet emerges as an important tool to
obtain the desired information. As the data transferred using networks is rapidly increasing …

Recently developed machine learning techniques, with emphasis on deep learning, are
finding their successful implementations in detection and classification of anomalies at both …

The rapid increase in the use of IoT devices brings many benefits to the digital society,
ranging from improved efficiency to higher productivity. However, the limited resources and …

As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …

In this paper, we execute anomaly detection over the computer networks using various
machine learning algorithms. We then combine these algorithms to boost the overall …

Abstract Anomaly-based Intrusion Detection Systems are critical components of modern
security systems. They often rely on Machine Learning (ML) to detect potential attacks and …

Due to the massive amount of the network traffic, attackers have a great chance to cause a
huge damage to the network system or its users. Intrusion detection plays an important role …

Supervisory control and data acquisition (SCADA) systems are used with monitoring and
control purposes for the process not to fail in industrial control systems. Today, the increase …

The Internet of Things (IoT) is a system that connects physical computing devices, sensors,
software, and other technologies. Data can be collected, transferred, and exchanged with …

The likelihood of suffering damage from an attack is obvious with the exponential growth in
the size of computer networks and the internet. Meanwhile, intrusion detection systems …