Growth in the number of devices and data has raised serious security concerns, that have
increased the importance of the development of advanced intrusion detection systems (IDS) …

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 …

The identification of malicious network traffic through intrusion detection systems (IDS)
becomes very challenging. This malicious network appears as a network protocols or …

Anomaly detection system in network, monitors and detects intrusions in the networking
area, which is referred to as NIDS, the Intrusion Detection System in Networks. There are …

Advances in communication and networking technology leads to the use of internet-based
technology in Industrial Control System (ICS) applications. Simultaneously to the …

Abstract Intrusion Detection System (IDS) has been developed to protect the resources in
the network from different types of threats. Existing IDS methods can be classified as either …

In today's cyber world, the demand for the internet is increasing day by day, increasing the
concern of network security. The aim of an Intrusion Detection System (IDS) is to provide …

In this work, we apply a two stage anomaly-based network intrusion detection process using
the UNSW-NB15 dataset. We use Recursive Feature Elimination and Random Forests …

With the increment of cyber traffic, there is a growing demand for cyber security. How to
accurately detect cyber intrusions is the hotspot of recent research. Traditional Intrusion …

Abstract Internet of Things (IoT) network is the latest technology which is used to connect all
the objects near us. Implementation of IoT technology is latest and growing day-by-day, it is …