Skip to content
DSML.KZ
Publications

Article · International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering · January 26, 2025

Tackling the anomaly detection challenge in large-scale wireless sensor networks

Tamara Kokenovna Zhukabayeva, Aigul Adamova, Lazzat Zholshiyeva, Yerik Mardenov, Nurdaulet Karabayev, Dilaram Baumuratova

Lazzat Zholshiyeva
Open via DOIPDF

Abstract

One of the areas of ensuring the security of a wireless sensor network (WSN) is anomaly detection, which identifies deviations from normal behavior. In our paper, we investigate the optimal anomaly detection algorithms in a WSN. We highlight the problems in anomaly detection, and we also propose a new methodology using machine learning. The effectiveness of the k-nearest neighbor (kNN) and Z Score methods is evaluated on the data obtained from WSN devices in real time. According to the experimental study, the Z Score methodology showed a 98.9% level of accuracy, which was much superior to the kNN 43.7% method. In order to ensure accurate anomaly detection, it is crucial to have access to high-quality data when conducting a study. Our research enhances the field of WSN security by offering a novel approach for detecting anomalies. We compare the performance of two methods and provide evidence of the superior effectiveness of the Z Score method. Our future research will focus on exploring and comparing several approaches to identify the most effective anomaly detection method, with the ultimate goal of enhancing the security of WSN.

Security in Wireless Sensor NetworksAnomaly Detection Techniques and ApplicationsNetwork Security and Intrusion Detectionanomaly detectionwireless sensor networksWSN security

More by Lazzat Zholshiyeva