Intrusion detection technology has received increasing attention in recent years. Many
researchers have proposed various intrusion detection systems using machine learning …

Abstract A Machine Learning (ML)-based Intrusion Detection and Prevention System (IDPS)
requires a large amount of labeled up-to-date training data to effectively detect intrusions …

Through the ongoing digitization of the world, the number of connected devices is
continuously growing without any foreseen decline in the near future. In particular, these …

Network intrusion detection systems (NIDSs) provide a better solution to network security
than other traditional network defense technologies, such as firewall systems. The success …

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 …

With the swift growth of Internet technology, various types of attacks and intrusions are taking
place over the Internet. Intrusion Detection Systems (IDS) are widely used to detect attacks …

One of the important technologies in present days is Intrusion detection technology. By using
the machine learning techniques, researchers were developed different intrusion systems …

Abstract 'Curse of dimensionality'and the trade-off between low false alarm rate and high
detection rate are the major concerns while designing an efficient intrusion detection system …

Network attacks are illegal activities on digital resources within an organizational network
with the express intention of compromising systems. A cyber attack can be directed by …

This article describes an experimental investigation into the inter-dataset generalization of
supervised machine learning methods, trained to distinguish between benign and several …