Abstract Network Intrusion Detection Systems (NIDS) have been extensively investigated by
monitoring real network traffic and analyzing suspicious activities. However, there are …

Network Intrusion Detection Systems (NIDS) have been extensively investigated by
monitoring real network traffic and analyzing suspicious activities. However, there are …

Ensemble classifier, by combining multiple classifiers, can often achieve better performance
than single classifiers in intrusion detection. Although some ensemble methods have been …

Autoencoder and conventional machine learning classifiers are widely used to design an
intrusion detection system (IDS). However, noise and corruption in the high-dimensional …

There is a growing need for systems that can be used to effectively detect and classify
intrusions in extensive network data exchanges. To this end, we propose Hi-MLIC, a …

Embedded systems, including the Internet of things (IoT), play a crucial role in the
functioning of critical infrastructure. However, these devices face significant challenges such …

The proliferation of wireless networks as a primary data transmission channel has brought
about a surge in data volume but also raised security threats and privacy concerns. Intrusion …

Background The ever increasing sophistication of intrusion approaches has led to the dire
necessity for developing Intrusion Detection Systems with optimal efficacy. However …

The growth of the internet has advanced information-sharing capabilities and vastly
increased the importance of global network security. However, because new and …

This research introduces bidirectional encoder representations from transformers-based IDS
(BERT-IDS), an innovative intrusion detection system (IDS) that leverages the BERT …