The Internet of Things (IoT) is a distributed system which is made up of the connections of
smart objects (things) that can continuously sense the events in their sensing domain and …

Recently, a new dimension of intelligent objects has been provided by reducing the power
consumption of electrical appliances. Daily physical objects have been upgraded by …

This paper surveys the deep learning (DL) approaches for intrusion-detection systems
(IDSs) in Internet of Things (IoT) and the associated datasets toward identifying gaps …

The Internet of Things (IoT) is a fact today where a high number of nodes are used for
various applications. From small home networks to large-scale networks, the aim is the …

Anomaly detection is important for time-critical Internet of Things (IoT) applications, such as
healthcare and emergency management. The recent introduction of Fog computing …

Clustering of big data has received much attention recently. In this paper, we present a new
clusiVAT algorithm and compare it with four other popular data clustering algorithms. Three …

As technology proceeds and the number of smart devices continues to grow substantially,
the need for ubiquitous context-aware platforms that support an interconnected …

Real-time environment monitoring and analysis is an important research area of Internet of
Things (IoT). Understanding the behavior of the complex ecosystem requires analysis of …

Optimum-path forest (OPF) is a graph-based machine learning method that can overcome
some limitations of the traditional machine learning algorithms that have been used in …

Due to the widespread functional benefits, such as supporting internet connectivity, having
high visibility and enabling easy connectivity between sensors, the Internet of Things (IoT) …