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 …

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 …

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 …

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

Abstract This paper proposes Hybrid Feature Selection Approach–Heterogeneous
Ensemble of Intelligent Classifiers (HyFSA-HEIC) for intelligent lightweight network intrusion …

Due to the frequency of malicious network activities and network policy violations, intrusion
detection systems (IDSs) have emerged as a group of methods that combats the …

Network security has emerged as a crucial universal issue that affects enterprises,
governments, and individuals. The strategies utilized by the attackers are continuing to …

Knowing a day's monitoring and analyzing events of network for intrusion detection system
is becoming a major task. Intrusion detection system (IDS) is an essential element to detect …

The objective of this article is to develop an intrusion detection model aimed at
distinguishing attacks in the network. The aim of building IDS relies on upon preprocessing …

Network security is a challenging task, as there is a tremendous growth of network-based
services and sharing of sensitive information on the network. Intrusion throws a serious risk …