Anomaly detection (AD) use within the network intrusion detection field of research, or
network intrusion AD (NIAD), is dependent on the proper use of similarity and distance …

The main task of an intrusion detection system (IDS) is to detect anomalous behaviors from
both within and outside the network system, and there have been increasing studies …

This paper describes the advantages of using the anomaly detection approach over the
misuse detection technique in detecting unknown network intrusions or attacks. It also …

This paper investigates the possibility of using ensemble algorithms to improve the
performance of network intrusion detection systems. We use an ensemble of three different …

The escalating frequency and sophistication of cyber threats pose significant challenges to
traditional intrusion detection methods. Signature-based misuse detection, hybrid detection …

Intrusion Detection System (IDS) is a tool for anomaly detection in network that can help to
protect network security. At present, intrusion detection systems have been developed to …

Intrusion detection system (IDS) alerts the network administrators against intrusive attempts.
The anomalies are detected using machine learning techniques such as supervised and …

The KDD Cup'99 data set has been widely used to evaluate intrusion detection prototypes,
most based on machine learning techniques, for nearly a decade. The data set served well …

In this study, since it is a laborious task to create cyber threat intelligence (CTI), a system that
will facilitate the generating of CTI with data mining techniques is proposed. With the system …

For the last decade it has become commonplace to evaluate machine learning techniques
for network based intrusion detection on the KDD Cup'99 data set. This data set has served …