Deep Learning Models for Cyber Security in IoT Networks

Abstract

As the number of connected devices grows, the internet of things (IoT) poses new security challenges for network activity monitoring. Due to a lack of security understanding on the side of device producers and end users, the majority of internet of things devices are vulnerable. As a result, virus writers have found them to be great targets for converting them into bots and using them to perform large-scale attacks against a variety of targets. The authors provide deep learning models based on deep reinforcement learning for cyber security in IoT networks in this chapter. The IoT is a potential network that connects both living and nonliving things all around the world. As the popularity of IoT grows, cyber security remains a shortcoming, rendering it exposed to a variety of cyber-attacks. It should be emphasized, however, that while there are numerous DL algorithms presently, the scientific literature does not yet include a comprehensive catalogue of them. This chapter provides a complete list of DL algorithms as well as their many application areas.