Industrial control systems (ICSs), supervisory control and data acquisition (SCADA) systems,
and distributed control systems (DCSs) are fundamental components of critical infrastructure …

The high dimension, complexity, and imbalance of network data are hot issues in the field of
intrusion detection. Nowadays, intrusion detection systems face some challenges in …

Context Recent years have seen a lot of attention into Deep Learning (DL) techniques used
to detect cybersecurity attacks. DL techniques can swiftly analyze massive datasets, and …

The application of cloud computing has increased tremendously in both public and private
organizations. However, attacks on cloud computing pose a serious threat to confidentiality …

This paper proposes an AI-powered intrusion detection method that improves intrusion
detection performance by increasing the quality of the training set and employing numerous …

Smart cities, businesses, workplaces, and even residences have all been converged by the
Internet of Things (IoT). The types and characteristics of these devices vary depending on …

Aiming at the problem that Sparrow Search Algorithm (SSA) may fall into local optima and
have slow convergence speed, a hybrid strategy improved sparrow search algorithm …

Cybersecurity threats have become more worldly, demanding advanced detection
mechanisms with the exponential growth in digital data and network services. Intrusion …

With the rapid development of the IoT (Internet of Things), the network data present the
characteristics of large volume and high dimension. Convolutional neural networks (CNNs) …

The Internet of Things (IoT) is a prominent and advanced network communication
technology that has familiarized the world with smart industries. The conveniently acquirable …