This study investigates the effectiveness of six prominent machine learning models—
random forest, decision trees, K-nearest neighbor, logistic regression, support vector …

Abstract Internet of Things (IoT) devices are widely used but also vulnerable to cyberattacks
that can cause security issues. To protect against this, machine learning approaches have …

The rapid increase in online risks is a reflection of the exponential growth of Internet of
Things (IoT) networks. Researchers have proposed numerous intrusion detection …

Network intrusion detection in the Internet of Things (IoT) framework has posed considerable
challenges in recent decades. A wide variety of machine-learning approaches are …

The rapid development of Internet of Things (IoT) networks has revealed multiple security
issues. On the other hand, machine learning (ML) has proven its efficiency in building …

The number of Internet of Things (IoT) devices has increased considerably in the past few
years, which resulted in an exponential growth of cyber attacks on IoT infrastructure. As a …

In recent years, there is a significant growth experienced in both data traffic as well as
dimensionality in Internet of Things (IoT) environment. In parallel, IoT networks are often …

The Internet of Things (IoT) ecosystem has experienced significant growth in data traffic and
consequently high dimensionality. Intrusion Detection Systems (IDSs) are essential self …

Internet of Things (IoT) technology has evolved significantly, transitioning from personal
devices to powering smart cities and global deployments across diverse industries …

The growing Internet of Things (IoT) landscape requires robust security; traditional rule-
based systems are insufficient, driving the integration of machine learning (ML) for effective …