More and more network traffic data have brought great challenge to traditional intrusion
detection system. The detection performance is tightly related to selected features and …

High-speed networks are becoming common nowadays. Naturally, a challenge that arises is
that the intrusion detection system (IDS) should timely detect attacks in huge volumes of …

Network intrusion detection plays a very important role in protecting computer network
security. The abnormal traffic detection and analysis by extracting the statistical features of …

This study discusses the application of deep learning technology in network intrusion
detection systems (IDS) and focuses on a new model named CNN-Focal. First, through the …

Network intrusion detection system (NIDS) plays an important role in network security. It can
detect the malicious traffic and prevent the network intrusion. Traditional methods used …

The intrusion detection models (IDMs) based on machine learning play a vital role in the
security protection of the network environment, and, by learning the characteristics of the …

Existing network intrusion detection models suffer such problems as low detection accuracy
and high false alarm rates in face of massive data traffic. Deep-learning models provide a …

Intrusion detection can identify unknown attacks from network traffics and has been an
effective means of network security. Nowadays, existing methods for network anomaly …

With the rapid development of network technology, a variety of new malicious attacks appear
while attack methods are constantly updated. As the attackers exploit the vulnerabilities of …

In recent times, Network-based Intrusion Detection Systems (NIDSs) have become very
popular for detecting intrusions in computer networks. Existing NIDSs can easily identify …