Intrusion Detection for Wireless Sensor Networks Using Parrot Algorithm

Abstract

Wireless sensor networks (WSN) have become widely used as technology in various industries, including the military, healthcare, and automation. regardless of their usefulness, WSNs are vulnerable to various cyber threats, such as denial of service (DoS), node replication attacks, and physical tempering. Due to the nature of WSNs being resource-constrained, Traditional IDS frequently fail to address these challenges, which leads to an increase in false alarm rates and limited accuracy in detection. This paper presents a new intrusion detection approach leveraging the Parrot Optimizer (PO) algorithm. The PO algorithm integrated the four major behavioral strategies to dynamically optimize IDS formation. The suggested IDS aims to improve computing efficiency, decrease false alarm rates, and increase detection accuracy by utilizing these flexible techniques, addressing the challenges of WSNs. The achieved results show that the implementation of bio-inspired algorithms enhances the performance of the IDS by improving the accuracy of detecting threats targeting the WSNs networks.