The problem of network intrusion detection poses innumerable challenges to the research
community, industry, and commercial sectors. Moreover, the persistent attacks occurring on …

Information security depends on Network Intrusion Detection (NID), which properly identifies
network threats. This work explores simulating a NID system by stacking ensemble …

Due to the extensive use of computer networks, new risks have arisen, and improving the
speed and accuracy of security mechanisms has become a critical need. Although new …

A robust network intrusion detection system (NIDS) plays an important role in cyberspace
security for protecting confidential systems from potential threats. In real world network, there …

Several studies have used machine learning algorithms to develop intrusion systems (IDS),
which differentiate anomalous behaviours from the normal activities of network systems. Due …

An efficient machine learning (ML) ensemble technique for categorizing Intrusion Detection
(ID) is proposed in this study. The tuning of the ML model's parameters is a critical topic …

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 …

Cyber-security garnered significant attention due to the increased dependency of individuals
and organizations on the Internet and their concern about the security and privacy of their …

Nowadays, one critical challenge of cybersecurity administrators is the protection of online
resources from network intrusions. Despite several academic and industry research …

One of the major developments in machine learning in the past decade is the ensemble
method, which finds highly accurate classifier by combining many moderately accurate …