Artificial intelligence based techniques capitulate better performance in identifying the
intrusions than other conventional approaches used in this field, but no single classifier is …

The exponential growth of Internet and network usage has necessitated heightened security
measures to protect against data and network breaches. Intrusions, executed through …

The growth of Internet and the services provided by it has been growing exponentially in the
past few decades. With such growth, there is also an ever-increasing threat to the security of …

The application of data mining techniques in intrusion detection has attracted considerable
attention from the research community. Ensemble learning can be used as an effective …

Nowadays, machine learning-based intrusion detection is a hot topic of research. Analysing
the nodes in the network or the underlying traffic can both be used to identify network …

One of the most significant requirements for improving the accuracy and performance of the
detection engine in an intrusion detection system (IDS) is to identify and pick just the most …

The main task of an intrusion detection system (IDS) is to detect anomalous behaviors from
both within and outside the network system, and there have been increasing studies …

With the increased dependence on the Internet, Network Intrusion Detection system (NIDs)
becomes an indispensable part of information security system. NIDs aims at distinguishing …

-Anomaly detection is a critical issue in Network Intrusion Detection Systems (NIDSs). Most
anomaly based NIDSs employ supervised algorithms, whose performances highly depend …

Security has been a crucial factor in this modern digital period due to the rapid development
of information technology, which is followed by serious computer crimes that, in turn, led to …