Nowadays, the ever-increasing complication and severity of security attacks on computer
networks have inspired security researchers to incorporate different machine learning …

Effectively detecting intrusions in the computer networks still remains problematic. This is
because cyber attackers are changing packet contents to disguise the intrusion detection …

The recent advancements in information and communication technologies have led to an
increasing number of online systems and services. These online systems can utilize …

In recent times, Network-based Intrusion Detection Systems (NIDSs) have become very
popular for detecting intrusions in computer networks. Existing NIDSs can easily identify …

Cloud computing environments provide users with Internet-based services and one of their
main challenges is security issues. Hence, using Intrusion Detection Systems (IDSs) as a …

The recent development and adoption of unmanned aerial vehicles (UAVs) is due to its wide
variety of applications in public and private sector from parcel delivery to wildlife …

The use of deep learning in various models is a powerful tool in detecting Internet of Things
(IoT) attacks and identifying new types of intrusion to access a better secure network. The …

A network intrusion detection model that fuses a convolutional neural network and a gated
recurrent unit is proposed to address the problems associated with the low accuracy of …

Network intrusion detection system is an essential part of network security research. It
detects intrusion behaviors through active defense technology and takes emergency …

Abstract The Intrusion Detection System plays a significant role in discovering malicious
activities and provides better network security solutions than other conventional defense …