An Enhanced Intrusion Detection Model Based on Improved kNN in WSNs

108Citations
Citations of this article
124Readers
Mendeley users who have this article in their library.

Abstract

Aiming at the intrusion detection problem of the wireless sensor network (WSN), consid-ering the combined characteristics of the wireless sensor network, we consider setting up a corre-sponding intrusion detection system on the edge side through edge computing. An intrusion detection system (IDS), as a proactive network security protection technology, provides an effective de-fense system for the WSN. In this paper, we propose a WSN intelligent intrusion detection model, through the introduction of the k‐Nearest Neighbor algorithm (kNN) in machine learning and the introduction of the arithmetic optimization algorithm (AOA) in evolutionary calculation, to form an edge intelligence framework that specifically performs the intrusion detection when the WSN en-counters a DoS attack. In order to enhance the accuracy of the model, we use a parallel strategy to enhance the communication between the populations and use the Lévy flight strategy to adjust the optimization. The proposed PL‐AOA algorithm performs well in the benchmark function test and effectively guarantees the improvement of the kNN classifier. We use Matlab2018b to conduct sim-ulation experiments based on the WSN‐DS data set and our model achieves 99% ACC, with a nearly 10% improvement compared with the original kNN when performing DoS intrusion detection. The experimental results show that the proposed intrusion detection model has good effects and practical application significance.

Author supplied keywords

Cite

CITATION STYLE

APA

Liu, G., Zhao, H., Fan, F., Liu, G., Xu, Q., & Nazir, S. (2022). An Enhanced Intrusion Detection Model Based on Improved kNN in WSNs. Sensors, 22(4). https://doi.org/10.3390/s22041407

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free