Networks provide a significant function in everyday life, and cybersecurity therefore
developed a critical field of study. The Intrusion detection system (IDS) becoming an …

In recent years, cybersecurity has attracted significant interest due to the rapid growth of the
Internet of Things (IoT) and the widespread development of computer infrastructure and …

Network intrusion detection has become a key technology to identify various network
attacks. The traditional shallow methods based intrusion detection faces with the problem of …

Abstract Machine learning techniques are widely used for network intrusion detection (NID).
However, it has to face the unbalance of training samples between classes as it is hard to …

An IDS (intrusion detection system) provides a foremost front line mechanism to guard
networks, systems, data, and information. That's why intrusion detection has grown as an …

Recently, network attacks launched by malicious attackers have seriously affected modern
life and enterprise production, and these network attack samples have the characteristic of …

Extreme learning machine (ELM) is a novel single-hidden layer feedforward neural network
to obtain fast learning speed by randomly initializing weights and deviations. Due to its …

The Internet of Things (IoT) is widely applied in modern human life, eg, smart home and
intelligent transportation. However, it is vulnerable to malicious attacks, and the current …

Deep learning has become a research hotspot in the field of network intrusion detection. In
order to further improve the detection accuracy and performance, we proposed an intrusion …

In this paper, a novel dual adaptive regularized online sequential extreme learning machine
(DA‐ROS‐ELM) is proposed to detect network intrusion. The ridge regression factor based …