In light of the escalating ubiquity of the Internet, the proliferation of cyber-attacks, coupled
with their intricate and surreptitious nature, has significantly imperiled network security …

Machine learning algorithms present a robust alternative for building Intrusion Detection
Systems due to their ability to recognize attacks in computer network traffic by recognizing …

Abstract Machine learning-based IDSs have demonstrated promising outcomes in
identifying and mitigating security threats within IoT networks. However, the efficacy of such …

Due to the widespread use of the internet, computer network systems may be exposed to
different types of attacks. For this reason, the intrusion detection systems (IDSs) are often …

Abstract The Internet of Things (IoT) and its applications are becoming ubiquitous in our life.
However, the open deployment environment and the limited resources of IoT devices make …

High-performing out-of-distribution (OOD) detection both anomaly and novel class is an
important prerequisite for the practical use of classification models. In this paper we focus on …

In the context of 6G technology, the Internet of Everything aims to create a vast network that
connects both humans and devices across multiple dimensions. The integration of smart …

The pervasive deployment of the Internet of Things (IoT) has significantly facilitated
manufacturing and living. The diversity and continual updates of IoT systems make their …

Intrusion detection systems (IDSs) analyze internet activities and traffic to detect potential
attacks, thereby safeguarding computer systems. In this study, researchers focused on …

Dyslexia is a learning disorder caused by difficulties in the brain's processing of letters and
words. This study used EEG recordings to detect dyslexia at a young age. EEG recordings of …