Energy evaluation of dependent malicious nodes detection in Arduino-based internet of things networks

Abstract

Detection of malicious nodes in the internet of things (IoT) network consumes power, which is one of the main constraints of the IoT network performance. To evaluate the energy-security trade-off for malicious node detection, this paper proposes an Arduino-based system for dependent malicious nodes (DMN) detection. The experimental work using Arduino and radio frequency (RF) modules was implemented to detect dependent malicious nodes in an IoT network. The detection algorithms were evaluated in terms of energy efficiency. The experiment comprises a coordinator node with five sensor nodes and varying malicious nodes. The results assess the detection algorithms in terms of distinguishing between normal and malicious behaviors and their impact on energy efficiency. The experiment demonstrated that the detection system could identify the malicious nodes. Additionally, the effect of increasing the number of sensors or malicious nodes on the suggested detection algorithm’s energy usage is evaluated.