Deep learning (DL), as one of the most active machine learning research fields, has
achieved great success in numerous scientific and technological disciplines, including …

As the IoT expands its influence, its effect is becoming macroscopic and pervasive. One of
the most discernible effects is in the industries where it is known as Industrial IoT (IIoT). IIoT …

Machine learning and deep learning techniques are widely used to evaluate intrusion
detection systems (IDS) capable of rapidly and automatically recognizing and classifying …

The rapid growth of the Internet of Things (IoT) has brought about a global concern for the
security of interconnected devices and networks. This necessitates the use of efficient …

This study presents a comprehensive exploration of the hyperparameter optimization in one-
dimensional (1D) convolutional neural networks (CNNs) for network intrusion detection. The …

Abstract The Internet of Things (IoT), as the information carrier of the Internet and
telecommunications networks, is a new network technology comprising physical entities …

Abstract The Internet of Things (IoT) scenario places important challenges even for deep
learning-based intrusion detection systems. IoTs are highly heterogeneous networks in …

The Industrial Internet of Things (IIoT) is a collection of interconnected smart sensors and
actuators with industrial software tools and applications. IIoT aims to enhance manufacturing …

The traditional support vector machine (SVM) requires manual feature extraction to improve
classification performance and relies on the expressive power of manually extracted …

Smoke is an early manifestation of forest fire. Accurate identification of smoke from forest
fires is crucial for the prevention and control of forest fires, which helps protect the ecological …