We present a comprehensive study on applying machine learning to detect distributed
Denial of service (DDoS) attacks using large-scale Internet of Things (IoT) systems. While …

The number of Distributed Denial of Service (DDoS) attacks using IoT devices has increased
in recent years. Reasons for this growth include the security limitations of IoT devices, the …

In recent times, distributed denial of service (DDoS) has been one of the most prevalent
security threats in internet-enabled networks, with many internet of things (IoT) devices …

Distributed denial of service (DDoS) attack is generally known as one of the most significant
threats to the internet of things (IoT). Current detection technologies of DDoS attacks are not …

With the emergence of technology, the usage of IoT (Internet of Things) devices is said to be
increasing in people's lives. Such devices can benefit the average individual, who does not …

In this paper we propose deep learning models for the cyber security in IoT (Internet of
Things) networks. IoT network is as a promising technology which connects the living and …

As the number of connected devices continues to rise, protecting those networks against
DDoS attacks is more important than ever. Due to IoT devices' specific features and limited …

The absence of standards and the diverse nature of the Internet of Things (IoT) have made
security and privacy concerns more acute. Attacks such as distributed denial of service …

A more widespread Internet of Things (IoT) device is performing a surge in cyber-attacks,
with Distributed Denial of Service (DDoS) attacks posing a major risk to the reliability and …

The phenomenal and continuous growth of diversified IOT (Internet of Things) dependent
networks has open for security and connectivity challenges. This is due to the nature of IOT …