In this paper, an intrusion detection system is introduced that uses data mining and machine
learning concepts to detect network intrusion patterns. In the proposed method, an artificial …

Intrusion detection has been playing a crucial role for making a computer network secure for
any transaction. An intrusion detection system (IDS) detects various types of malicious …

Network intrusion detection system is an essential part of network security research. It
detects intrusion behaviors through active defense technology and takes emergency …

Recently, Networks have developed quickly during the last many years, and attacks on
network infrastructure presently are main threats against network and information security …

After digital revolution, large amount of data are produced from diverse networks from time to
time. Hence security of this data is more important. So, there is a need to automate this …

The most pressing issue in network security is the establishment of an approach that is
capable of detecting violations in computer systems and networks. There have been several …

As the number of intrusions is increasing, intrusion detection of systems and network
infrastructures Systems (IDS) is now an active research area to develop reliable and efficient …

The internet connected devices are prone to cyber threats. Most of the companies are
developing devices with built-in cyber threat protection mechanism or recommending …

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 …

Network intrusion is a growing threat with potentially severe impacts, which can be
damaging in multiple ways to network infrastructures and digital/intellectual assets in the …