With an increasing number of services connected to the internet, including cloud computing
and Internet of Things (IoT) systems, the prevention of cyberattacks has become more …

Intrusion detection is one of the most prominent and challenging problem faced by
cybersecurity organizations. Intrusion Detection System (IDS) plays a vital role in identifying …

Cloud computing is gaining significant traction and virtualized data centers are becoming
popular as a cost-effective infrastructure in telecommunication industry. Infrastructure as a …

Many studies utilized machine learning schemes to improve network intrusion detection
systems recently. Most of the research is based on manually extracted features, but this …

Anomaly-based machine learning-enabled intrusion detection systems (AML-IDSs) show
low performance and prediction accuracy while detecting intrusions in the Internet of Things …

With the rapid advancements of ubiquitous information and communication technologies, a
large number of trustworthy online systems and services have been deployed. However …

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

Our paramount task is to examine and detect network attacks, is one of the daunting tasks
because the variety of attacks are day by day existing in colossal number. The program …

In this paper, Big Data and Deep Learning Techniques are integrated to improve the
performance of intrusion detection systems. Three classifiers are used to classify network …

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 …