To solve the problem of low accuracy and high false‐alarm rate of existing intrusion
detection models for multiple classifications of intrusion behaviors, a network intrusion …

A network intrusion detection model that fuses a convolutional neural network and a gated
recurrent unit is proposed to address the problems associated with the low accuracy of …

Imbalanced datasets greatly affect the analysis capability of intrusion detection models,
biasing their classification results toward normal behavior and leading to high false‐positive …

In recent days, the Intrusion Detection System (IDS) has become a fundamental component
of network security for an organization. Several approaches have been proposed and …

The need for Network Intrusion Detection systems has risen since usage of cloud
technologies has become mainstream. With the ever growing network traffic, Network …

There's been a series of datasets with regards to network intrusion detection in recent years,
and a significant number of studies has also been carried out using these datasets. In this …

Intrusion detection system (IDS) plays an important role in network security by discovering
and preventing malicious activities. Due to the complex and time-varying network …

Security remains as a key role in this internet world owing to the fast expansion of users on
the internet. Numerous existing intrusion detection approaches were introduced by …

The connectivity of devices through the internet plays a remarkable role in our daily lives.
Many network-based applications are utilized in different domains, eg, health care, smart …

The intrusion detection system can distinguish normal traffic from attack traffic by analyzing
the characteristics of network traffic. Recently, neural networks have advanced in the fields …