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 …

Applications of internet-of-things (IoT) are increasingly being used in many facets of our
daily life, which results in an enormous volume of data. Cloud computing and fog computing …

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

The massive modern technical revolution in electronics, cognitive computing, and sensing
has provided critical infrastructure for the development of today's Internet of Things (IoT) for a …

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 …

Due to the prompt expansion and development of intelligent systems and autonomous,
energy-aware sensing devices, the Internet of Things (IoT) has remarkably grown and …

Abstract The Smart Grid's objective is to increase the electric grid's dependability, security,
and efficiency through extensive digital information and control technology deployment. As a …

Nowadays, the Internet of Things (IoT) devices and applications have rapidly expanded
worldwide due to their benefits in improving the business environment, industrial …

Detecting intrusion in network traffic has remained a problematic task for years. Progress in
the field of machine learning is paving the way for enhancing intrusion detection systems …

Software vulnerabilities have always been an essential issue in cyberspace, for which many
vulnerability detection techniques have been investigated. Among them, deep learning …