Energy-Efficient DRL for Securing IoT Devices

Abstract

With the ever-increasing expansion of the world via IoT, the IoT requires these urgent and basic requirements, security and energy efficiency. Thus, deep reinforcement learning has emerged as an interesting subfield of machine learning for studies of protecting IoT devices. This paper explains how DRL could be incorporated into IoT security system to achieve enhanced energy efficiency and protection against more attacks.

Issues with security maintenance by energy consumption management are presented and solutions for an effective energy consumption in IoT setting are suggested. A number of use cases are employed to illustrate the possible promise that the integration of DRL can offer to IoT security processes.