As cyberattacks become more intelligent, it is challenging to detect advanced attacks in a
variety of fields including industry, national defense, and healthcare. Traditional intrusion …

Software-Defined Networking (SDN) is an emerging paradigm, which evolved in recent
years to address the weaknesses in traditional networks. The significant feature of the SDN …

Machine learning and deep learning techniques are widely used to evaluate intrusion
detection systems (IDS) capable of rapidly and automatically recognizing and classifying …

Recently, computer networks faced a big challenge, which is that various malicious attacks
are growing daily. Intrusion detection is one of the leading research problems in network …

The data is exposed to many attacks during communication in the network environment. It is
becoming increasingly essential to identify intrusions into network communications …

In recent years, all real-world processes have been shifted to the cyber environment
practically, and computers communicate with one another over the Internet. As a result, there …

Network Intrusion Detection Systems (NIDS) to find potential security breaches. However,
security attacks tend to be unpredictable. There are many challenges to develop a flexible …

This study reviews and analyses the research landscape for intrusion detection systems
(IDSs) based on deep learning (DL) techniques into a coherent taxonomy and identifies the …

The Internet of Things (IoT) is a promising technology that allows numerous devices to be
connected for ease of communication. The heterogeneity and ubiquity of the various …

The network attacks are increasing both in frequency and intensity with the rapid growth of
internet of things (IoT) devices. Recently, denial of service (DoS) and distributed denial of …