With the rapid advancements of ubiquitous information and communication technologies, a
large number of trustworthy online systems and services have been deployed. However …

Nowadays, network attacks are the most crucial problem of modern society. All networks,
from small to large, are vulnerable to network threats. An intrusion detection (ID) system is …

Machine learning (ML) algorithms are often used to design effective intrusion detection (ID)
systems for appropriate mitigation and effective detection of malicious cyber threats at the …

Network security becomes indispensable to our daily interactions and networks. As attackers
continue to develop new types of attacks and the size of networks continues to grow, the …

In recent years, all real-world processes have been shifted to the cyber environment
practically, and computers communicate with one another over the Internet. As a result, there …

Machine learning techniques are being widely used to develop an intrusion detection
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …

Many studies utilized machine learning schemes to improve network intrusion detection
systems recently. Most of the research is based on manually extracted features, but this …

Network assaults pose significant security concerns to network services; hence, new
technical solutions must be used to enhance the efficacy of intrusion detection systems …

Security concerns for Internet of Things (IoT) applications have been alarming because of
their widespread use in different enterprise systems. The potential threats to these …

Networks play important roles in modern life, and cyber security has become a vital research
area. An intrusion detection system (IDS) which is an important cyber security technique …