A Self-Learning Framework for the IoT Security

Abstract

The internet of things (IoT) is a complex system of heterogeneous devices connected to a network. While IoT can significantly add value to people's everyday activities around the world, there are numerous security risks and privacy breaches imposed by the IoT landscape. Traditional security solutions are not applicable for the IoT as they require high-end processing capacity. The objective of this chapter is two-fold. Firstly, it provides a comprehensive summary of the recent advancements in the IoT and identifies their vulnerabilities. Secondly, it proposes the paradigm of self-learning as an intelligent and sustainable mechanism that is capable of automatically detecting suspicious activities in the IoT. Overall, this chapter presents a contemporary coverage of the recent developments in the IoT scene, the security and privacy challenges confronting the security experts, a proposal of a self-learning framework for performing health check of the IoT environment, and finally a set of high-level implementation guidelines and conclusions.