The growing adoption of the Internet of Things (IoT) has brought a significant increase in
attacks targeting those devices. Machine learning (ML) methods have shown promising …

The evolution of mobile technologies has introduced smarter and more connected objects
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …

Machine learning (ML) has been emerging as a viable solution for intrusion detection
systems (IDS) to secure IoT devices against different types of attacks. ML based IDS (ML …

The insecure growth of Internet-of-Things (IoT) can threaten its promising benefits to our
daily life activities. Weak designs, low computational capabilities, and faulty protocol …

DDoSim, a simulation testbed for mimicking real-world, large-scale botnet DDoS attacks, is
presented. DDoSim offers various capabilities, including running user-specified software …

With the proliferation of IoT devices, securing the IoT-based network is of paramount
importance. IoT-based networks consist of diversely purposed IoT devices. This diversity of …

Many security issues have come to the fore with the increasingly widespread adoption of
Internet-of-Things (IoT) devices. The Mirai attack on Dyn DNS service, in which vulnerable …

The Internet of Things (IoT) is a rapidly growing subset of our modern computing
architecture, and as such, provides significant new attack surface. The history of IoT has …

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 …

In today's IoT smart environments, dozens of MCU-based connected device types exist such
as HVAC controllers, smart meters, smoke detectors, etc. The security conditions for these …